Taiwan Semiconductor Manufacturing Company (TSMC) (Taipei: 2330 and NYSE: TSM) may be the most important business most people have never heard of. Right now, you're probably carrying products that it has made. Most consumers recognise names such as Apple and Nvidia. Yet behind many of the products they sell sits a Taiwanese manufacturer responsible for turning their designs into reality.

Every day, billions of people rely on devices powered by chips produced by TSMC. The company's influence stretches far beyond smartphones. From artificial intelligence to consumer electronics, much of the modern digital economy ultimately depends on a business with headquarters on an island roughly 100 miles off the coast of China.

What makes TSMC remarkable is not simply its scale, but the way it achieved it. Unlike most technology giants, it did not become dominant by creating the best consumer products or developing a monopoly over software. Instead, it positioned itself as a neutral supplier to an industry filled with fierce competitors. In effect, TSMC became the Switzerland of the semiconductor world, doing business with everyone and doing so in secrecy.

How Morris Chang founded TSMC

That strategy was the brainchild of Morris Chang, a veteran semiconductor executive who spotted a flaw in the industry's business model and built an entire company around solving it. Nearly four decades after it was founded, his insight sits at the centre of the global technology industry.

Chang never set out to build one of the world's most important firms. For 25 years, he worked at Texas Instruments, rising high to run its global semiconductor business. During those years, Chang noticed a problem. Brilliant engineers regularly designed innovative chips, but turning those designs into products required vast sums of money.

In the 1970s and 1980s, semiconductor firms were expected to do everything themselves. Designing chips was only half the job. Companies also needed expensive factories, specialised equipment and the expertise to run them. The result was an industry dominated by a handful of large, vertically integrated firms.

Then Chang's own career took an unexpected turn. In 1983, aged 52, he was passed over for the top job at Texas Instruments and left the company. After a brief spell in a senior role at another American chip company, he received an unusual offer. The Taiwanese government wanted to build a domestic electronics industry and was looking for someone with Silicon Valley experience to lead the effort. Chang accepted.

He arrived in Taiwan with decades of semiconductor experience and a conviction that copying America would be a mistake. Taiwan lacked the design expertise, customer relationships and global brands needed to compete. But Chang had spent years watching another problem unfold. The industry was full of talented chip designers who could not afford to manufacture their ideas. What if somebody built the chips for them?

That simple question led to the creation of TSMC in 1987. At the time, the idea looked absurd. Bringing a chip to market required access to a fabrication plant, or “fab”. The industry believed serious companies should own these factories themselves. In practice, that meant chip designers relying on one of the industry giants.

That created another problem. The company manufacturing your chip was often also a competitor. Handing over your most valuable intellectual property required a leap of faith. Chang's solution was that TSMC would make chips for anyone willing to pay, but would never design products of its own.

In 1987, that sounded like madness. When Chang went looking for investors, many of the industry's biggest names rejected him. Texas Instruments and Intel both declined his offer. A factory without its own products looked like a recipe for bankruptcy. How could a manufacturer survive without guaranteed demand?

In the end, Chang persuaded the Dutch electronics group Philips and several wealthy Taiwanese families to back the venture. Even then, enthusiasm was limited. Philips largely viewed the investment as a way of supporting the Taiwanese government's ambitions rather than as a compelling commercial opportunity. It intended liquidating its investment early. Potential customers were hardly more enthusiastic. Many designers saw little reason to outsource manufacturing. A company that only made chips for other people seemed unnecessary.

By now, Chang was a 56-year-old executive pitching an untested business model in an industry convinced it could never work. Then, fortune presented an opportunity. In 1988, Intel found itself short of manufacturing capacity. Faced with the prospect of disappointing customers, it reluctantly turned to TSMC for help. Intel's engineers arrived in Taiwan expecting a low-cost, unsophisticated subcontractor. Instead, they found a world-class operation run by one of the industry's most experienced executives. Passing Intel's quality standards was not easy, but once TSMC secured the American giant's approval, attitudes across the industry changed quickly. If Intel trusted TSMC, others reasoned, perhaps they could too.

That endorsement transformed the trajectory of the company. Designers no longer needed to spend billions building factories before launching a new product. Instead, they could focus on what they did best – designing chips, and letting TSMC handle the rest. Without TSMC, it's unlikely that Nvidia could have existed, nor could a host of other chip companies.

A new generation of semiconductor firms emerged, freed from one of the industry's biggest barriers to entry. While rivals competed to design better chips, TSMC focused on becoming the best manufacturer in the world. By choosing not to compete with its customers, the company turned neutrality into a competitive advantage. That decision would prove far more powerful than anyone imagined. But the success of TSMC's model created an obvious question: if it was such a good idea, why didn't somebody copy it?

Many tried, but almost all failed. For years, Samsung looked like the most credible challenger. The South Korean giant had deep pockets and decades of manufacturing experience. The problem was that Samsung was also a competitor. Unlike TSMC, Samsung sold smartphones and consumer electronics under its own brand. That created a dilemma for customers. Why hand your most valuable chip designs to a firm that might one day compete against you? No customer wrestled with that question more than Apple.

During the early years of the iPhone, Samsung made many of Apple's processors. The arrangement worked, but it became increasingly awkward as the two companies emerged as fierce rivals in the smartphone market. By the early 2010s, they were fighting a series of patent disputes. Apple found itself in the strange position of relying on one of its biggest competitors to make some of its most important components.

TSMC offered an escape route. With the launch of the A8 processor in 2014, Apple shifted production to Taiwan. The move was risky, but Apple concluded that the benefits outweighed the costs. TSMC's neutrality had become one of the most valuable assets in the technology industry. Today, many of Silicon Valley's biggest rivals manufacture their chips at TSMC. Apple, Nvidia, AMD and Qualcomm all rely on the same company, despite competing aggressively in their own markets.

Samsung's problem was a conflict of interest; Intel's was something different: success. For decades, Intel dominated the semiconductor industry. Its factories were among the most advanced in the world. However, the company became increasingly focused on its own products. When Apple approached Intel in the mid-2000s about supplying chips for what would become the first iPhone, Intel declined.

Management believed the opportunity was too small to justify the investment. It was one of the most expensive misjudgements in the history of the technology industry. By the time Intel recognised its mistake, Apple had moved on and TSMC was becoming the manufacturing partner of choice for a new generation of chip designers. When Intel later attempted to open its factories to outside customers, its manufacturing systems had been built around Intel's products, not the needs of third-party designers.

Other competitors couldn't keep up with the investment needs. GlobalFoundries, an American rival, spent years trying to keep pace before effectively giving up on leading-edge manufacturing in 2018. The company concluded that each new generation of chip technology required so much investment that the returns no longer justified the risk.

China's national champion, SMIC, faces a different challenge. Western export controls have restricted access to advanced manufacturing equipment, making it difficult to compete at the industry's frontier.

TSMC's greatest advantage

TSMC's greatest advantage is not its technology, because that can be copied. Its real advantage is the business model Morris Chang created nearly four decades ago. The company sits at the centre of the semiconductor industry, serving customers that often compete with one another. That position generates enormous scale, which in turn funds the next generation of factories and equipment.

The most advanced chips require ultraviolet lithography machines built by the Dutch company ASML. Each cost more than £275 million. A state-of-the-art fab may contain dozens of these machines, helping to push the cost of a new facility beyond £15 billion before production even begins. That creates a problem for potential rivals.

Customers will not trust an unproven manufacturer with their most important products, especially if they don't have advanced fabs. Yet building a state-of-the-art factory requires billions of pounds before those customers appear. Having already achieved enormous scale, TSMC now largely escapes this trap. The company controls roughly 92% of advanced chip manufacturing and generates the cash needed to fund the next generation of technology.

In 2026 alone, TSMC expects to spend nearly £45 billion on new factories and equipment. Few companies in the world could contemplate spending that much. None can do so with the same confidence of earning a return. The result is a powerful feedback loop. Scale attracts customers. Customers generate cash. Cash funds new factories. New factories attract even more customers.

Every year that cycle turns, TSMC becomes harder to catch as the price of entry rises ever higher. That scale gives TSMC another advantage: it allows customers to help fund its expansion. Most manufacturers have to build factories first and hope demand follows. Today, TSMC often works the other way around. Some of its largest customers commit billions of pounds years before new facilities begin production, effectively helping to finance the next generation of capacity.

At the end of 2024, TSMC held more than £7.3 billion of customers' deposits. As production ramped up on newer technologies, some of that money was recognised as revenue, but the balance remained substantial. Technology companies are willing to tie up enormous sums because access to TSMC's manufacturing has become critical to their own growth plans. This arrangement shifts much of the risk away from TSMC.

When companies such as Nvidia sign long-term agreements worth billions of pounds, they provide “visibility” – confidence in management forecasts – that few industrial businesses can match. New factories can be built with a high degree of confidence that demand will be waiting when they open. That helps explain why TSMC can continue investing through industry cycles.

AI is a game-changer for the semiconductor industry

For years, Apple was the company's most important customer. The iPhone generated the predictable demand that allowed TSMC to refine successive generations of manufacturing technology and steadily expand its lead. Now a new force is reshaping the industry. AI has become the biggest driver of demand for advanced semiconductors. Training and running large AI models requires vast quantities of computing power, creating an arms race among technology companies desperate to secure enough chips.

The biggest beneficiary has been Nvidia. In 2025, Nvidia overtook Apple as TSMC's largest customer, generating more than £18 billion of revenue for TSMC and accounting for roughly a fifth of total sales. The shift says a great deal about how quickly AI has altered the economics of the technology industry, but the opportunity extends beyond chip design.

Producing cutting-edge AI processors is one of the most demanding manufacturing tasks in the world. The chips themselves are larger, more complex and more difficult to assemble than those used in smartphones. As demand has exploded, bottlenecks have emerged throughout the supply chain. For TSMC, that has translated into even greater pricing power.

The world's largest technology firms are competing for a limited supply of advanced manufacturing capacity. Many have little choice but to accept TSMC's terms because there are few credible alternatives. AI has reinforced the advantages of specialisation. Developing a leading-edge AI chip already costs hundreds of millions of pounds. Building the factory to make it would require billions more. As AI pushes the technological frontier forward, the advantages of specialisation are becoming even more pronounced.

But TSMC's dominance creates a problem. Most of the world's most advanced semiconductor manufacturing remains concentrated in Taiwan. That has become a concern for governments, particularly as tensions between China and Taiwan have intensified. A disruption to TSMC's operations would ripple through the global economy.

Smartphones, data centres, AI systems and countless other technologies depend on its chips. Under pressure from the US and other governments, it's begun expanding overseas. The largest investment is a vast complex in Phoenix, Arizona. Similar projects are underway in Japan and Europe.

Building advanced factories in the US is estimated to be roughly 50% more expensive than doing so in Taiwan. Labour costs are higher, experienced engineers are harder to find and supply chains are less developed. TSMC has reportedly had to transfer experienced staff from Taiwan and create thousands of new operating procedures to support its US operations. Yet even these higher costs have not weakened the company's position.

Customers are willing to pay a premium for chips manufactured on US soil. For many, securing a politically safer supply chain is worth the extra expense. In an ironic twist, efforts to reduce dependence on TSMC have largely demonstrated how dependent the world has become on its expertise.

The future looks bright for TSMC

Whether the company can maintain its current position forever is another question. The semiconductor industry has a long history of dominant firms losing their edge, while geopolitical tensions surrounding Taiwan remain an ever-present risk. Governments are spending heavily to build alternative sources of supply and rivals continue searching for ways to close the gap.

However, history suggests writing off TSMC would be unwise. For nearly 40 years, the company has repeatedly adapted to changes in technology, customers' demands and the structure of the industry. It has survived downturns, outlasted competitors and continued strengthening its position at the heart of the digital economy. The story of TSMC is ultimately the story of how a company became indispensable. In an industry defined by relentless change, that may be its most remarkable achievement.

None of this means TSMC is a bargain. Investors are well aware of the company's strengths and the shares have performed exceptionally well over the past decade. As a result, the stock trades on a valuation that reflects high expectations for future growth. Still, TSMC has qualities that are difficult to find elsewhere. It occupies a dominant position in one of the world's most important industries, enjoys deep relationships with many of the largest technology companies on the planet and continues to invest heavily to maintain its lead.

Most importantly, investors do not need to predict which company will ultimately win the AI race. Whether the future belongs to Nvidia, AMD or some future challenger, there is a good chance that their chips will still be manufactured by TSMC. That does not guarantee attractive returns from today's share price. But betting against the company has rarely been a profitable strategy. For investors seeking exposure to long-term growth in technology and AI, TSMC remains one of the highest-quality businesses in the market.

This article was first published in MoneyWeek's magazine. Enjoy exclusive early access to news, opinion and analysis from our team of financial experts with a MoneyWeek subscription.

In May 2025, Dario Amodei, the CEO of AI company Anthropic, said that the technology his company is helping push forward could drive unemployment up to 10%-20% in the next one to five years and wipe out half of all entry-level white-collar jobs, as Josh Tyrangiel points out in The Atlantic.

Jim Farley, the CEO of Ford, has estimated that AI will eliminate half of all white-collar jobs in a decade. Sam Altman of OpenAI has opined that it is just a matter of time before we see a billion-dollar company staffed by just one person.

That the advent of a new technology has given rise to predictions of disastrous consequences is hardly new. But that the prophets of doom come not from the ranks of the usual suspects, but from the makers of the new technology and those most in a rush to adopt it, is.

So, are they right? AI is clearly already transforming work, says Tyrangiel. Companies including Meta, Amazon, Walmart, and JPMorganChase have recently announced lay-offs due to “automation”.

Three academics from the Stanford Digital Economy Lab have found that entry-level jobs that are exposed to disruption from AI have already seen a 13% decline since late 2022. So the transformation may already be under way, even if it's too early to be sure (other factors could explain the decline and the evidence is sparse and mixed).

If that transformation unfolds slowly and the economy adjusts quickly, then we may, as economists reassure us, be fine, or even better off in aggregate. But if AI instead triggers a rapid reorganisation of work, compressing years of change into months, affecting roughly 40% of jobs worldwide – as the IMF projects – then the consequences could be huge.

Is AI actually any good for us?

Which will it be? Let's remember that humanity has been automating work for 250 years, as technology analyst Benedict Evans has pointed out. History shows that every wave of automation has destroyed whole classes of jobs and created new ones. The process may be painful for some, but over time and in the aggregate the result has been greater prosperity.

Two concepts from economics give us confidence that this time is unlikely to be different. The first is the “lump of labour fallacy” – the misconception that there is a fixed amount of work to be done and that if some work is taken by a machine then there will be less work for people. But if it becomes cheaper to use a machine to make a pair of shoes, say, then the shoes are cheaper, more people can buy shoes, and they then have more money to spend on other things, and we discover new things we need or want, and new jobs get created.

The second concept is Jevons Paradox. In the 19th century, the Royal Navy ran on coal and people worried about what would happen when the coal ran out. Don't worry, said the optimists: steam engines are getting more efficient, so they'll use less and less coal. Not at all, said economist William Stanley Jevons: if we make steam engines more efficient, then they will be cheaper to run, and we will use more of them and use them for new and different things, so more efficient steam engines means we will use more coal.

That paradox has been at work in relation to white-collar work for a long time, says Evans. In the 1880s, typewriters and carbon-copy paper meant that clerks could produce more than ten times the output of the days when they copied out documents one at a time by hand. The result for clerical employment? Far more clerks were hired. If one clerk can do the work of ten, then perhaps you might want to do more of the work that clerks do – more analysis, or manage more inventory, say. You might build a different and more efficient business that is only possible because of the new technology.

It was the same story when, much later, digital spreadsheets were introduced that could do at the click of a button what might previously have taken a whole team of accountants all week. Employment for accountants went up.

The most recent study into what AI is doing to jobs seems to confirm that this is indeed what is happening this time, as Noah Smith reports on Substack. A study by Ara Kharazian, Lisa Simon and Ryan Stevens, researchers at US technology start-ups Ramp and Revelio Labs, examined private data to determine what happens when companies start using generative AI. The answer is that they hire more humans. The number of entry-level jobs rose, too. So it seems that AI is “still mostly a complement to human labour rather than a substitute” for it, says Smith. For now at least, AI is “behaving pretty much like a normal technology”.

AI is just software

That's the usual pattern, and if AI did indeed start to progress at the rates feared and with the consequences predicted, it would be “unprecedented in human history”, says The Economist. New technologies have never spread fast enough to make large numbers of people unemployed for long periods of time because the diffusion of the technology always proceeds slowly.

To see why that is unlikely to be different this time, remember that AI is just software, as Tyrangiel points out. And the thing about software is that “people hate it almost as much as they hate change”. Before AI can transform a company, it has to access data and be woven into existing systems. A “trade secret of most Fortune-500 companies is that they still run critical functions on lumbering, industrial-strength mainframe computers that almost never break down and therefore can never be replaced”. Integrating such legacy tech with AI would mean big changes involving lots of people with strong opinions about the “right” way to proceed. Meanwhile, months pass, then years – and “the CEO still can't understand why the miracle of AI isn't solving all of their problems”.

Indeed, the idea that “one magic piece of software” will change everything instantly and override all the complexity of real people, real companies and the real economy “sounds like classic tech solutionism, but turned from utopia to dystopia”, says Evans. The reality looks rather different, as Zeynep Tufekci shows in The New York Times. Firms that have experimented with fully automating functions such as customer service have been burned. The result has been scammers talking chatbots into handing over control of key functions, promising refunds or incredible deals, such as a new car for $1. The bot taking orders at McDonald's proved “wildly dysfunctional”.

The key thing to understand is that these incidents are not the result of errors, but of the technology functioning as it is designed to do. Currently existing AI technologies are “not reasoning machines” – they simply produce answers that are probable based on the data they've been trained upon. They have no common sense or intelligence. AI can “do many things with astounding efficiency”, especially if those things are formal and structured and can be tested and checked in real time. Most jobs are simply not like that and still require “good old-fashioned human intelligence”.

This doesn't mean the “job apocalypse” definitely won't happen, says The Economist. Maybe this time will be different. Perhaps the technology will transform in ways we cannot yet predict. If so, you may know the apocalypse by these signs: sharply rising productivity combined with weak real-wage growth in the US, the world's frontier economy. This would show up as an increase in GDP per person above the 2.5% upper limit that is the historical norm in frontier economies and a simultaneous jump in corporate profits, reflecting that the gains from higher output were flowing to capital, not labour. Another sign would be big job losses in lots of industries, showing up in a recession. Which jobs vanish in the next recession will “give a hint about the shape of the AI world to come”.

Is there actually any sign of any of this happening? Not really. The labour market “certainly is not cracking yet”, says The Economist. “The share of the OECD's working-age population with a job keeps breaking records, unemployment across the club of mostly rich countries is just 5%, and America employs more people than ever in ‘AI-exposed' industries, such as law.” American graduates have been struggling to find jobs since before the launch of ChatGPT fired the starting gun on the AI revolution in late 2022. Many economists foresee relatively little disruption ahead. Those at America's Bureau of Labour Statistics think the country will add 5.2 million jobs between 2024 and 2034, increasing total employment by 3%.

Robots can't do your job

There are broader reasons for scepticism. The heaviest users of AI have recently been scrambling to curtail its use as the cost of using it outweighs the gains. Surprisingly few people use the technology on a regular basis and the share of companies in the OECD that have adopted AI remains small (about 20% for the latter, although figures for both individual use and company uptake vary widely across different studies, depending on what is deemed to count.) The basic problem here is that most people just don't know what AI is supposed to do for them, as Evans has argued. There's a box you can type stuff into, and you get text in response. Often the text is roughly right, but precisely wrong. For how many people will that be life-changing? As Pablo Picasso perceptively saw in 1968, “Computers are useless. They can only give you answers.”

The likelihood is that AI will not so much replace jobs, as make certain tasks easier and quicker for some people. Generally, says Evans, jobs are a complex mesh of things that we might not even be able to explain explicitly. You may have a good idea of just why a chatbot is never going to be able to do your job, for example, but will be impressed if someone says that it can of course already do the job of a lawyer or a doctor. The blunt truth is we do not know just what is involved in jobs we are confidently predicting will be gone tomorrow, nor do we know how AI will change them, if at all.

What we should most fear is fear itself. A recent poll found that 70% of Americans believe that AI will reduce their employment opportunities, says Robert Shiller, also in The New York Times. That fear could in itself have economic consequences. When millions and millions of people make economic decisions based upon negative expectations, there is a risk that the fear can actually “help birth the reality”. The leaders of Silicon Valley should learn to do better than peddle alarmist narratives in the hope that the resulting media attention will highlight how powerful their latest AI model is. They will find it harder to sell their wares in future if the result is an economy paralysed by fear and recession.

This article was first published in MoneyWeek's magazine. Enjoy exclusive early access to news, opinion and analysis from our team of financial experts with a MoneyWeek subscription.

Artificial intelligence (AI) could be embedded into every aspect of a financial services business by 2030 as millions of savers and investors are already making use of the tools, research by the Financial Conduct Authority (FCA) has found.

The City watchdog asked executive director Sheldon Mills to review how advances in AI could transform retail financial services.

The Mills Review, published this week, found one in five UK adults - equivalent to 11 million UK adults - are already open to AI making decisions for them in areas such as pensions and investments but there are concerns about trust and control.

The review found that while AI has the potential to improve access, personalisation and efficiency, it could also amplify risks associated with fraud, cybersecurity, consumer harm and market concentration.

Mills said: “Artificial intelligence will transform financial services by 2030. It creates significant opportunities for consumers, firms and the wider economy. This report sets out a roadmap for how industry regulators and government can prepare for the next phase of AI-driven change in our world-leading financial services sector.”

Here is how the FCA expects AI to reshape financial services.

Changing roles in financial services

The regulator suggests human roles in financial services will change.

It highlights that many firms are already piloting and rolling out AI tools and by 2030 they could be more independent and cover every function from customer support and underwriting to compliance, claims and product design.

AI may become the main method by which they process information, serve customers, and evidence outcomes, the FCA suggests.

This could mean the role of people within firms changes from operators close to each decision towards collaborators, approvers and, eventually observers who monitor outcomes and step in when systems move outside agreed parameters.

The FCA said: “This is a substantial organisational shift, requiring new skills and a clearer account of what human oversight actually involves.

“Firm governance will extend existing model risk management to cover more complex systems and deeper reliance on third-party providers. Successful AI deployment should lift productivity and support economic growth, though the benefits will reach consumers only where firms remain accountable and markets stay competitive enough to pass them on.”

The review suggests the human role becomes one of challenge, judgement and review rather than direct production of every output.

The rise of agentic AI

Consumers are increasing using AI applications to act on their behalf and automatically follow preset instructions, known as agentic AI, and the FCA predicts this could grow in financial services.

This may involve easier bank switching, embedding insurance into other platforms, auto-rebalancing in savings and investments and pension pot consolidation.

The FCA said: “Overtime, AI systems will move beyond offering information and recommendations towards trusted AI agents that can act continuously for consumers within agreed limits, providing ongoing financial management and optimising people’s financial lives.

"If done well, this could help consumers achieve more while doing less, addressing long-standing problems such as low switching, advice and protection gaps, and improving outcomes for people with lower financial capability.”

The FCA warns that consumers will still need to be able to oversee, understand and challenge AI-driven decisions, especially when things go wrong, the report adds: “Unequal access to high-quality applications risks widening inclusion gaps - but well-designed AI systems also present an opportunity to radically improve outcomes for those who need more support.”

Changes in market power

The rise of AI could reshape who holds the power in financial services.

Investors and savers may flock to well-known investment platforms or providers now but the FCA says AI has the potential to drive greater beneficial competition in financial services and to support new entrants.

This could make the suppliers more powerful and there are risks of dependance on a few technology firms.

The FCA said: “Control of the AI-mediated customer interface may become a major source of market power.

"As consumers rely on agents to search, compare and transact, the owner of that AI layer may influence which products are visible, how choices are ranked and where value is captured, shifting the customer relationship away from financial services providers.”

AI risks

While AI could help consumers manage their finance more effectively, the FCA review wants that there will also be more fraud risks.

The report said: “Deepfakes, synthetic identities and personalised social engineering are taking fraud and cyber risks into a new era and changing how fraud and cyber-attacks are conducted. Existing weaknesses can be exploited far more quickly than before, and defenders will need to keep pace.

“Defensive, supervisory and enforcement capability must evolve at least as quickly as the threat. To remain effective, firms, regulators and their partners will need access to many of the same AI capabilities as those used by attackers.

"They will also need to share the right information with those best placed to act, when it matters and before harm escalates.”

Is AI regulated?

Artificial intelligence isn’t regulated but Mills suggests that existing rules such as the Consumer Duty and Senior Managers Regime should cover some of the risks associated with how savers and investors may use AI.

The review does add that regulation may have to evolve though to focus on shared models between firms though rather than focusing on individual conduct.

It also suggests that the FCA review AI tools such as ChatGPT and Claude to assess if there are regulatory overlaps and risks in the results generated.

Commenting on the report, Amal Jolly, chief executive of the AI company Saturn, which specialises in financial advice, said: "AI brings new opportunities to close the advice gap, improving the financial lives of millions of adults, but as this report shows it also brings huge risks.

“In financial services, AI is the new Wild West: consumers are left with no protection. Only 9% of people have access to regulated human financial advisers, but 100% of people have access to ChatGPT and other AI platforms. This is not just a theoretical problem, but can cause real harm to people who are entrusting major life-changing financial decisions to unregulated AI.”

SpaceX has joined the Nasdaq 100, meaning passive funds that track the index will now automatically hold positions in the company, which listed on 12 June.

SpaceX (NASDAQ:SPCX) joined the index today (7 July), a week after it was added to the Russell 1000 Index (29 June).

Bloomberg reported SpaceX could look forward to an estimated $5.4 billion of inflows as a result of ‘forced’ buying by index funds that track these two indices.

Elon Musk’s space exploration company was fast-tracked for inclusion following rule changes by the index providers, put in place to reflect the unprecedented size of some initial public offerings (IPOs) coming to market.

Nasdaq’s new rules now allow freshly listed companies to be included in as few as 15 trading days, rather than its previous minimum period of three months after an IPO.

What will SpaceX index inclusion mean for flows?

Nasdaq says globally, there is around $1.4 trillion in assets tracking its component companies’ combined market capitalisation (market cap) of $31.5 trillion, around half of which do so through exchange-traded funds (ETFs). The other half is in derivative products, such as futures and options.

The Nasdaq 100 index represents the largest 100 companies, excluding financials, listed on the Nasdaq Stock Market. Often described as a tech-focused index, it contains all ‘Magnificent 7’ names – Alphabet, Amazon, Apple, Tesla, Meta, Microsoft and Nvidia. But it also contains many other companies with a value of $100 billion or more from healthcare, industrials and materials, for example, with representation across 10 of the 11 standard industry classification sectors.

When a stock joins an index like the Nasdaq 100, funds tracking that index are effectively forced to buy its shares so that they still reflect the index. This creates additional demand for a stock and could push up its share price.

The UCITS version of Invesco’s Nasdaq-100 ETF (LON:EQQQ) is the largest Nasdaq-tracking ETF available to UK investors. Barclays Smart Investor platform lists it as the seventh most popular purchase during the week of 26 June to 2 July.

Alongside the uplift from index fund inclusion, several investment banks have issued positive analyst statements on SpaceX, marking the end of the ‘quiet period’ that typically follows an IPO. Morgan Stanley, Goldman Sachs, UBS and Bernstein Research are among the names backing the stock with ‘buy’ recommendations or equivalent, based on asset strength and long-term growth prospects.

Baltimore-based Constellation Energy, a $90 billion company, generates electricity on a vast scale. And AI's voracious appetite means that electricity is now becoming a very valuable commodity, and the companies that can generate it reliably, cleanly and at scale will see a lot more attention than they're currently getting.

Investors have re-priced entire industries, assuming AI will transform the global economy. Electricity gets less attention, yet the chips, AI models and data centres are all useless without power. Vast data centres consume enormous quantities of power to train and run increasingly powerful models. Electric vehicles, battery factories, semiconductor plants, air-conditioning systems, industrial re-shoring and electrification more generally are all pulling in the same direction.

Tap into the great electrification with Constellation Energy

Constellation Energy (Nasdaq: CEG) owns the largest fleet of nuclear reactors in the US and has more nuclear power stations than anyone else at a time when hyperscalers are searching for reliable and cost-efficient power. Investors increasingly view Constellation less as a utility and more as the owner of scarce infrastructure – an essential asset – which explains its appeal as a long-term growth stock.

Constellation Energy currently generates about 10% of US clean energy. It produces enough electricity to power about 27 million US homes. It is the largest nuclear-energy company in the country and its power stations sit alongside a fleet of gas, hydro, wind, solar, geothermal and oil-fired assets. These produce 55 gigawatts (GW) of capacity.

To put that into perspective, the UK's recent winter peak demand for electricity was typically around 60GW, according to the National Energy System Operator. Constellation has 2.5 million customer accounts across the US and counts 80 of the country's 100 biggest firms by revenue among them.

Results in May showed first-quarter sales up 64% from $6.8 billion to $11.1 billion year-on-year. While impressive, roughly $2 billion-$3 billion of that reflected the acquisition of Calpine, a largely gas and geothermal power generator. Constellation Energy generated roughly $25 billion of revenue over 2025 as a whole. Earnings per share were $2.74 in the quarter, up 28% over the year and beating analysts' estimates by 14 cents.

The firm's nuclear fleet achieved an excellent 92.3% capacity factor, meaning its reactors were producing electricity at close to their maximum potential for almost the entire period. Management isn't seeing any slowdown in demand from the hyperscalers, with projected spending levels continuing to rise to reflect the growing need for computer processing.

Management has reaffirmed its expectation of 2026 earnings per share of around $11, up from $9.39 and $8.67 in 2025 and 2024 respectively. It's targeting 20%-plus annual earnings per share through to 2029 led by higher prices and rising demand, including improved long-term contracts.

Analysts have $13.50 pencilled in for 2027. Their 12-month share-price target is $362, about a third higher than now. Of course, in a world hungry for electricity, existing generation capacity may prove considerably more valuable than investors currently assume.

Don't chase the chips

The curious thing is that investors can currently buy a company expected to grow earnings by more than 20% annually at a valuation broadly in line with the wider market. Usually, investors are asked to pay a substantial premium for that combination of growth and strategic importance. The market's comfortable paying premium valuations for businesses that consume computing power. But it's a lot less interested in businesses that sell the vast amounts of electricity that makes such computing possible now and in the future. Look beyond that “utility” label and there is an opportunity to be had.

The immediate objection is that electricity is hardly scarce. If demand goes up, the power generators can build more capacity. But new power stations need planning permission, endless environmental reviews, financing, engineering expertise, political support and years of construction. And then transmission networks need upgrading.

This is where Constellation Energy's nuclear fleet becomes particularly interesting. Investors spend a great deal of time discussing technological moats. Yet there may be few barriers to entry that are more formidable than a collection of fully operating nuclear reactors. The market's growing interest in Constellation Energy reflects a simple reality: it already owns large-scale electricity infrastructure that is built, connected and delivering cleanly at scale. Building more is possible, but doing so quickly is another matter.

Nobody can yet say with certainty which company will dominate AI. What already seems clear, however, is that the modern economy wants far more electricity. Investors have spent the first phase of the AI boom chasing the chips. The second phase may belong to those pumping the power. Investors may find it easier to back the latter than gamble on the eventual winners of the AI race.

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Dr Douglas Williams is a veteran senior executive and board member for several biotech companies. During his time at Biogen, ZymoGenetics, Amgen Immunex and Seattle Genetics, he was involved in the development of several multibillion-dollar treatments, including Enbrel, Tecfidera and Spinraza.

Matthew Partridge: The time and cost of clinical trials has been seen as one of the big stumbling blocks to the emergence of new drugs. Do you see any developments that could help speed up the process?

Douglas Williams: Anything you can do to speed up the process is beneficial – after all, time is money. I think the real benefits will come as we become more efficient at targeting better-defined populations of patients [those who meet highly specific and uniform criteria, thus making it easier to gauge the exact effect of drugs]. In a field with a high rate of failure, improving the chances of success by even a small percentage can have a huge impact on the bottom line.

Matthew Partridge: Have the recent changes at the US Food and Drug Administration (FDA), the regulator of federal health, helped or hindered the clinical-trial process?

Douglas Williams: It's all a bit chaotic at present. You're seeing reversals of long-standing policy with political interference in what should be scientifically driven decisions. The “willy-nilly” nature of the Department of Government Efficiency's (DOGE) cuts has also led to a brain drain at the FDA itself, with some of the most experienced staff leaving.

Matthew Partridge: The FDA is seen as a gold standard when it comes to getting drugs approved first. Could there come a day when drug companies start looking to regulators in Europe or elsewhere?

Douglas Williams: This is already happening at the front end of the clinical-trial process, where Australia has become a key destination for early phase-one studies [the first of three stages of clinical trials, when scientists test the safety of the drug]. The regulatory process there is relatively quick and streamlined, making it a cost-effective place to run studies. And Australia's consolidated healthcare system makes the process of finding patients and enrolling them in studies more efficient.

Similarly, I've been working with Chinese companies and the system's low cost of capital, overall efficiency and rapid trial process are remarkable.

Matthew Partridge: The Trump administration has been threatening tariffs on drugs. Do you see geopolitical issues as a major risk for the drug and biotechnology sectors?

Douglas Williams: I do think there is logic in wanting to onshore some of the manufacturing for crucial drugs. There has been this enormous migration offshore from the US on the manufacturing side. So to try to bring some of that back, certainly for vital components of key drugs, makes a lot of sense. But there are surely better ways to achieve this than tariffs, which are a blunt instrument.

Matthew Partridge: Do you think America's dominance of the biotech and drug sectors is at risk?

Douglas Williams: I think that it's very much at risk for a variety of reasons. There definitely need to be some major changes to the FDA to bring the regulatory regime closer to what's happening in China and Australia. Firms are moving to the latter for early-stage studies, although people will still want to enrol patients in later-stage trials in the US and Europe.

The other thing that's happening in the US that I worry about from a longer-term perspective is that the reduction in the National Institutes of Health's funding for basic science grants is chasing away a whole generation of PhD students and postdoctoral candidates. This is already starting to create a hole in the pipeline for talent, and the longer this goes on, even if it's just for the four years of the current administration, the longer it will take to rebuild.

The engine driving the innovation that creates new companies in the sector and allows for new intellectual property to be created and new breakthroughs to take place is being eroded.

Matthew Partridge: What should the UK do to make itself more friendly to biotech and pharma companies?

Douglas Williams: The UK can streamline the process of starting studies and enrolling patients quickly and easily through the NHS, and raising patients' awareness of the trials on offer. More specifically, it could learn a lot from what the Chinese have done around streamlining the rules governing which particular regulatory bodies you need to secure approval from to begin a trial.

Matthew Partridge: Turning to the wider sector, GLP-1 drugs are changing the way we deal with weight-loss, diabetes and perhaps other conditions as well. Do you think the firms that pioneered GLP-1s are going to be able to stay ahead of the competition, or will it be like the computer industry, where firms such as IBM were unable to maintain their control of the industry?

Douglas Williams: The biotech industry is based on the expectation that there will be a rotation of dominance, as patents only last a certain amount of time before rivals are allowed to produce generic versions of a drug, causing prices and profits to collapse. But until that happens, the first-movers in this area, such as Novo Nordisk and Eli Lily, will dominate it. They've also pursued new approaches for delivering the drug – shifting from injectables to oral tablets, for instance. So they're creating scope for multiple waves of innovation, which could extend their dominance.

However, biotech is ultimately all about building a better mousetrap: there are other young companies coming in that are attempting new methods that don't come with the side effects, such as muscle loss, that are associated with the GLP-1s, for instance.

Matthew Partridge: Are there any other big leaps forward that could take place in the next five years or so?

Douglas Williams: I find the work around the role of sleep in dementia and brain conditions very interesting, and the idea that deep sleep can help combat those conditions is certainly an elegant theory. Neurology, in general, has become much hotter from an investment perspective. I'm involved with several companies in the neuropsychiatry sector, including being chair of Draig Therapeutics, a Cardiff-based company developing treatments for major depressive disorder.

The analogy people have used is that neurology is going to become the next oncology, where the precision approach to well-defined populations of patients is going to dominate drug development. So, you'll essentially be treating slices of the populations that have a particular broad definition of a disease.

Matthew Partridge: What about advances in medical imaging, such as MRIs and CT scans?

Douglas Williams: During my career, I was involved in the early development of some of the first approved drugs in the amyloid reduction arena and what really turned the tide was being able to understand what these drugs were doing inside the brain; it's hard to do without some way of looking at the target. I think faster and more effective scanning technology has already fed back into neurology-drug development.

Matthew Partridge: Do you think in five years' time the range of treatments for neurological conditions, things like dementia, could be radically different?

Douglas Williams: Yes, there's so much activity in this area, a reflection of the problems posed by ageing populations.

Matthew Partridge: How is AI going to change drug development?

Douglas Williams: It depends on your definition of drug development. Taking the all-encompassing view, where a fully integrated company does the discovery, drug development, manufacturing and sales and marketing, it will change the whole process. One example is in manufacturing. Already, we can take real-time data from the bioreactors that are used to manufacture proteins, and AI can use this to tweak the process to make sure that you maximise productivity. There's an increasing amount of work now on using AI in the clinical-trial process, both in terms of designing the trials and dealing with back-office operations.

I've been in this field for 40 years, and it's remarkable what some of the young companies I'm involved in are doing with AI. I'm optimistic that in the next ten years, we'll start to see the impact of AI on designing new molecules and finding new drugs too.

Matthew Partridge: Do you think that there will still be a need for actual scientists, rather than AI alone, to be involved?

Douglas Williams: Without question. If you ask ChatGPT or Claude a question, how the question is worded matters a lot, and that's where the role of the scientist really shows itself – the better the question, the better the answer. So, there will always be a place for the human element in terms of driving science.

Matthew Partridge: Have investors in the sector learnt to tune out political noise and focus on the long-term growth story?

Douglas Williams: I think so. Stock market valuations have risen while mergers and acquisitions have proliferated, which is always healthy because it gives investors capital to put back to work. So a virtuous circle has developed. There's never been a more amazing time in terms of the tools that we now have for drug development, while our understanding of biology continues to expand.

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Some analysts have proclaimed that AI is more important and will be more transformative for human development than the creation of the railways. With the world's largest technology companies now spending more than $1 trillion a year expanding their presence in the market, there's no doubt this theme will dominate for the foreseeable future.

However, as investors focus on the so-called hyperscalers – Alphabet, Microsoft and Amazon – which are building their AI infrastructure at an alarming rate, as well as chip manufacturers such as Nvidia and Micron, which are supplying the industry, not much attention is being directed to the infrastructure that will power this revolution. This is where bottlenecks are now starting to throttle growth.

The energy grid needs an upgrade to power AI

The critical one is the power grid. In the US, for example, the grid is around 50 years old and was not designed to handle the current level of rapid growth in demand. The graphics processing units, or GPUs, that underpin AI data centres today are vastly more energy-intensive than their previous counterparts.

Research compiled by Goldman Sachs and JPMorgan estimates that by 2027, AI server racks will require 50 times more power than the equivalents that formed the backbone of cloud infrastructure five years ago.

The computing power of any facility consumes only around 60% of the total energy requirement. The rest is taken up by cooling systems and other infrastructure.

As the hyperscalers expand, they are learning that Silicon Valley moves much faster than the rest of the world. GPUs have become 50 times more energy-intensive over the past five years, but global energy output has risen by just 1%-3% per year. In the real world, it can take five to seven years just to secure permits and sign initial contracts to build the power infrastructure. This has started to change in the past two years, but there's still a long way to go. According to the International Energy Agency (IEA), global electricity consumption by data centres will double to 945 terawatt-hours (TWh) by 2030, representing roughly 3% of global demand for electricity. That's roughly the same as adding 34 Hinkley Point C-scale nuclear-power plants to the global grid. Between 2025 and 2030, data-centre electricity consumption is expected to grow by 15% per year, four times the growth rate of total electricity consumption across all other sectors.

Electricity consumption from accelerated AI data centres, the most intensive units that train AI models, will rise by 30% annually. In the worst-case scenario, the IEA estimates that global data-centre demand for electricity could exceed 1,700 TWh by 2035, nearly 5% of global demand for electricity. If the industry becomes more efficient at utilising power, that figure could fall to 970 TWh. If the electricity industry fails to rise to the challenge, demand could be limited to 700 TWh by 2030, nearly 25% below the base-case scenario.

This bottleneck is most apparent in the US and China, where the most time and energy are being spent on AI development. China and the US will account for nearly 80% of global data-centre electricity consumption growth to 2030, according to the IEA. The US, in particular, is facing a projected power access shortfall ranging from 10.4 gigawatts (GW) up to 49GW by 2028, even though projections from the US Energy Information Administration (EIA) show the grid adding 86GW of new utility-scale electricity-generation capacity in 2026, the largest single-year rise since 2002.

Rise of the ‘Bring Your Own Power’ model for data centres

To get around some of these issues, data-centre providers are increasingly seeking to innovate. The “Bring Your Own Power” (B-Y-O-P) movement, for example, is bypassing grid-connection bottlenecks by building on-site microgrids, utilising utility-scale batteries, solar panels, fuel cells and wind and gas turbines. Elsewhere, data-centre operators and hyperscalers are working with utility providers to purchase and install natural-gas power stations.

Data-centre providers are also shifting their attention to gas-rich zones such as the Permian Basin in Texas and New Mexico, where natural-gas pipeline capacity is severely constrained (gas prices recently dropped below zero despite the war in the Middle East). Companies are building off-grid data centres directly at these extraction sites, monetising otherwise stranded gas that would have zero economic value.

For example, Microsoft (Nasdaq: MSFT) and Chevron (NYSE: CVX) are partnering to build a $7bn, 2.5GW off-grid natural-gas power complex in Pecos, Texas, specifically to supply Microsoft's AI data centres under a 20-year agreement. Williams (NYSE: WMB), a pipeline company transporting a third of the natural gas moving across the US, is developing “Neo”, a $2.3 billion project utilising gas turbines paired with battery energy storage systems (BESS) for a major hyperscaler. This is the company's fifth BYOP agreement.

Some providers are also turning to AI to help mitigate AI's impact on power grids. A recent report from the World Economic Forum notes that “power-flexible” AI factories can dynamically modulate their electricity use, throttling energy-intensive tasks such as model training during periods of stress for the grid and routing more mundane tasks (such as answering simple questions on ChatGPT) to other locations. This flexibility enables data centres to capitalise on the volatile nature of renewable-energy generation.

Energy prices take the strain

As the utility market has struggled to adapt to the surge in demand for electricity, prices have responded. Wholesale electricity prices have jumped across all global markets, and the impact is particularly acute in the US. In some eastern US states, prices have risen 76%. According to the Bureau of Labour Statistics, across the country, electricity prices are rising nearly 61% faster than general inflation. The entire supply chain is feeling the pain. Lead times for the production and delivery of grid equipment have skyrocketed. Standard electricity transformers now take 128 weeks to deliver, compared with just 16 weeks in 2019. In some cases, specialist transformers are being delayed for nearly three years.

The production of highly efficient combined-cycle gas turbines can take up to four years, more than double the length recorded in 2022, and across the entire supply chain analysts put the average price rise at 30% across all grid equipment. There's also been a dramatic shortfall in the number of construction engineers and electricians, with the figure put at nearly 300,000 construction engineers and electricians in the US over the next decade. There are no quick solutions to any of these problems. While producers try to scale up output to meet rising demand, it looks as if they will continue to hold all the cards for the next five years at least.

There are three ways for investors to play this trend. There are the companies that generate power, those that make equipment for power stations, such as gas turbines, and those that manufacture cables and equipment to transmit electricity from A to B.

Tap into the AI energy boom with power players

One of the hottest plays is GE Vernova (NYSE: GEV). Created as part of General Electric's break-up, GE Vernova specialises in designing, manufacturing and maintaining equipment for the power-generation industry. Its technology provides roughly 25% of the world's electricity and the group has an order backlog of $163 billion, or 3.5 times sales. Its order backlog for gas turbines sits at around 100GW – around 2.5 times the UK's total daily electricity consumption. UBS has modelled 14% annual organic sales growth for the group through 2028 based on its current order backlog, with a 22.7% Ebitda margin by 2028, up from 8.4% in 2025.

Unlike the GPUs that power data centres, which have an estimated average life of around five to eight years, gas turbines can last up to three decades, locking in a multi-decade service contract for Vernova. The firms also offers kit for firms running older units (20 years and upwards) to help improve reliability and efficiency. Despite this growth and its key market position, there's a lot priced into the stock at a mid-30s price-earnings (p/e) ratio, but UBS argues that the valuation is worth it given the revenues and potential for margin growth.

Rolls-Royce (LSE: RR), which came close to a government bailout in the pandemic, is now one of the world's most sought-after power engineers. For the year to the end of 2025, the company reported a 12% jump in underlying revenue to £20 billion and underlying operating profit rose by 41% to £3,462 million, equating to a margin of 17.3%. Profit growth was driven primarily by the power-systems arm (25% of revenue), where the divisional margin expanded by 430 basis points to 17.4%. The firm put this down to “growth driven by data centres” and it's hoping its “power-dense” next-generation diesel and gas engines will continue to drive growth. Its technology is in demand as data-centre providers seek alternatives to bypass ever increasing queues for power-grid connections. The FTSE 100 company recently noted that orders across gas and diesel engines in the first quarter was around 50% higher than last year and March was a record month. Power Systems' order backlog was £7.3 billion at 31 March.

But Power Systems isn't just about data centres. The business also produces battery energy-storage systems and engines for Leopard tanks. What's more, last year Rolls-Royce conducted the world's first successful test of a high-speed marine engine running on pure methanol. There's also the company's nuclear business. A long-time supplier of nuclear reactors to the Royal Navy, Rolls-Royce has begun moving into the civil market with its small modular reactors (SMRs). In June last year, Rolls-Royce's SMR was chosen as the sole provider in the Great British Energy – Nuclear competition to build three SMR units in the UK.

Rolls-Royce SMR also received a strategic investment from CEZ Group, alongside a commitment for up to six units in the Czech Republic. In mid-June, the division was selected to deliver three SMRs on Sweden's west coast in partnership with Videberg Kraft. Based on current estimates, Rolls-Royce is trading at a forward p/e of 38.2, falling to 32.7 in 2027, according to average analysts' estimates. Those have ticked higher after the company's latest upbeat trading update and Berenberg has pencilled in a forecast of £8 billion of share buybacks over 2026-2028, split by £2.5 billion in 2026, £2.7 billion in 2027 and £2.8 billion in 2028, with scope for more cash returns if cash flow beats projections over the coming months.

A US peer of Rolls-Royce is BWX Technologies (NYSE: BWXT). Like its UK counterpart, BWX has the backstop of a US Navy contract in its back pocket to support its general operations – it has been the sole nuclear-fuel provider to the US Navy for more than 70 years. It's now seeking to grow in the civil market, where it provides specialised, complex, high-precision equipment used in nuclear reactors, including steam generators, reactor-pressure vessels and piping. It has an order backlog of $8.7 billion (around 2.2 years of revenue) bolstered by the recent $1.4 billion set of contracts through the US Naval Nuclear Propulsion Programme. However, at nearly 50 times forward earnings, there's a lot baked into the current share price.

How to invest in the undersea cable kings

The energy-transfer market is more concentrated than the other two potential investment segments. The renewable-energy transition has triggered an unprecedented global demand for ultra-high-voltage subsea cables to transport power from offshore wind and solar sites to urban centres, a market that did not exist 15 years ago. It's currently dominated by a European oligopoly consisting of Prysmian (Milan: PRY), Nexans (Paris: NEX), and NKT (Copenhagen: NKT). These companies emerged as the winners in what was an incredibly competitive market, with lots of smaller players that couldn't keep up with the capital-spending commitments required to manufacture vast undersea sea cables.

High-voltage direct-current (HVDC) cables can be thick, and they must be kept completely straight during manufacturing, which often requires companies to hang them inside skyscraper-high warehouses. The capital required to build this infrastructure runs into the billions. For example, the 500-kilometre Eastern Green Link 2 (EGL2) project in the UK, the single largest ever investment in electricity-transmission infrastructure in the country, has a price tag of £4.3 billion, with £2.7 billion of that for the cable itself.

The global high-voltage submarine cable market is expected to grow at a compound annual growth rate of 17.3% over the next decade. Production hit 7,000 kilometres in 2025, an all-time high, and the major players are rapidly ramping up production. Prysmian is drawing on its experience in this market to expand in the DC inside-building segment – essentially wiring up the power inside data centres. The company believes it will become a one-stop shop for data-centre construction contracts, building long-haul subsea connections and shore-based transmission infrastructure, and then for infrastructure throughout the building to power GPUs and air-conditioning units.

Management has estimated that overall global demand for DC power will expand at a compound annual growth rate of 33% over the next five years, with the bulk of this coming from AI-related data-centre growth. Analysts have pencilled in earnings growth of 25% for 2026, followed by 23% for 2027, with a net profit of €1.7 billion projected for 2027, up nearly ten times from 2020. Based on these projections, the shares are trading at a 2027 p/e of 24.9, which doesn't seem too demanding for a high-growth business operating in an oligopoly.

Prysmian is around three times the size of its smaller peers, both of which are using their growing profitability and cash flow to expand into newmarkets. Of the two, Paris-listed Nexans is the cheapest, trading at a 2028 p/e of around 13 based on management's growth targets. The group has laid out a road map to achieve an adjusted Ebitda of €1.2 billion by 2028 (up from about €750m) through growth in its three main businesses: PWR-Transmission, PWR-Grid and PWR-Connect. Sales are already locked in with a backlog of €7.9 billion by early 2026, enough to cover sales through to 2028.

Deals will also be a major part of the future growth plan. It recently added US-based Republic Wire to the stable to bulk out its US arm (about 15% of revenue). Republic reported sales of €52millionmn in its latest fiscal year and will be a key conduit for Nexans to enter the US data-centre market. Nexans plans to use Republic Wire's established channels to sell its own comprehensive offering of medium-voltage and grid technology into premium US end markets. The acquired business is currently finalising a significant expansion programme, which will increase its production capacity by about 30% by the end of 2026.

How to play coal

Another FTSE 100 company that's strategically well placed is National Grid (LSE: NG). Although still small compared with the US and Chinese markets, the UK data-centre market is the largest in Europe. National Grid believes demand for electricity in the UK will increase by 30% by 2035 to 290GW with a 90% increase in installed generation capacity to 370 TWh. To meet this demand, the company is investing £41 billion by 2031 to expand its regulated asset value by 60% to £60 billion. It is also going to invest £29 billion to expand its US business to a regulated asset value of £45 billion, with a focus on its key markets of New York and Massachusetts. The shares currently look cheap, selling at a forward p/e of 13.9.

One sector investors could also consider is coal. According to Global Energy Monitor, more than 2,200GW of coal-powered generation still operates worldwide, with another 710GW under development. China is scaling up its coal-output market to meet increased demand for energy and a total of 32 countries are proposing, or building, new coal plants to meet the growing need for power. At the beginning of June, Donald Trump announced plans to build two new coal plants in Alaska and West Virginia under the Defence Production Act, adding to the US coal fleet, which supplies 15% of the country's demand for power. Alliance Resource Partners (Nasdaq: ARLP), Peabody Energy Corp (NYSE: BTU) and Warrior Met Coal Inc (NYSE: HCC) are three left-of-field plays worth considering here.

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The invisible hand of the facilities management (FM) industry operates in almost every large commercial building. Someone is maintaining the chillers and the fire-suppression system. Someone is cleaning the floors. Someone, in theory, knows whether the heating, ventilation and air-conditioning (HVAC) unit on the fourth floor is three months from failure. This industry, sprawling, unglamorous and rarely covered by analysts, generates north of $4 trillion in annual global revenue. It is also in the early stages of a bifurcation that will create some genuinely interesting investment opportunities and destroy a remarkable amount of value for those who pick the wrong horse.

The core problem with facilities management is that it has spent decades solving the wrong problem. It has been focused on fixing things rather than understanding why things break in the first place. It has been reactive when its customers need it to be predictive. It has been operational when the most sophisticated clients are desperate for something more strategic. And it has been unable to provide evidence of the value it affords. Every contract renewal thus defaults to a conversation about cost that facilities management companies are badly placed to win.

Technology is now changing this, but not in the way most industry observers have assumed. The narrative for many years has been that some form of unified digital platform, a so-called single pane of glass, would allow facilities managers to own the data and therefore control the strategic conversation with their clients. That narrative is broadly correct. What it has missed is who actually ends up controlling that glass.

The problem with facilities management companies

The smart money is on the original equipment manufacturers (OEMs). Siemens, Schneider Electric, Johnson Controls and Trane Technologies have all made aggressive acquisitions of integrated workplace-management software businesses in the last three years. They control the mechanical and electrical systems that generate the core telemetry. They are now buying the platforms that interpret that data.

CBRE and JLL, two giant US commercial property services and investment groups, have responded with their own investments in technology, and CBRE in particular has built something genuinely differentiated. Its technology stack, running from raw asset data through AI-driven performance optimisation to a generative AI interface for facility managers, is meaningfully ahead of most traditional facilities management rivals.

More importantly, CBRE has made a strategic choice that I think is correct and underappreciated: it self-delivers the engineering and maintenance work where risk and complexity are high and it subcontracts almost everything else. This keeps the business focused on what it does best, avoids the diseconomies of running enormous low-margin cleaning and catering workforces, and keeps the conversation with customers at the level where CBRE's technology and insight capabilities actually add value.

The integrated model that FM firms ISS, Coor, Mitie and ABM Industries have pursued, employing vast workforces across subsectors from cleaning and engineering to food service, has struggled with low margins, volatile earnings and weak cash generation.

It is not that these companies are badly run. It is that the model is structurally disadvantaged. Every dollar of capital reinvested in innovation or process improvement flows through to a smaller share of the overall business when that business is simultaneously managing electricians, cleaners, security guards and caterers. The benefits of scale are harder to capture. Best practice is harder to standardise. The most talented engineers would often rather work for a pure-play technical services company than be one service line among eight.

Compass Group found the right path

There are exceptions and they are instructive. Compass Group has built one of the most impressive records in global services by staying almost entirely focused on food. Its management and performance framework is a masterclass in what happens when a large, decentralised services firm imposes a common operating language and a small number of clearly defined drivers of value across an entire organisation.

The framework ties every decision to one of five levers determining profit or loss – from client retention and consumer participation through to labour scheduling and overhead control. It sounds almost boring in its simplicity. It has produced two decades of best-in-class margin delivery at scale.

My preferred name among facilities management stocks is Bravida (Stockholm: BRAV), the technical services group that installs and maintains the electrical, HVAC and plumbing systems in buildings across Sweden, Denmark, Norway and Finland. It does not try to do everything.

Bravida focuses almost entirely on facilities management engineering delivered through a network of 330 branches providing the local density and proximity to customers that makes the economics work. When you build genuine scale in a single technical discipline, you can standardise ways of working, invest properly in training and certification, attract the best engineers, and compound efficiency gains year after year.

Bravida has been through a difficult patch, hit by a Swedish construction downturn, a governance failure in one branch that has since been closed and prosecuted, and some bad debts from a large customer. The share price has derated significantly. I think that creates an opportunity. The underlying business model is sound, the structural drivers for technical building services are strongly positive, and the company's internal focus on operational excellence is exactly the kind of self-improvement culture that separates durable compounders from cyclical operators.

The privately owned CFS, or Churches Fire & Security, is another business worth watching. It operates in the UK fire safety and electronic-security market, an arena driven by tightening regulation, historic underinvestment and alarming fragmentation that sees roughly 2,000 small operators competing with essentially no scale advantages. CFS has now absorbed over 70 businesses, each integrated fully within three to six months. Revenue has jumped to £100 million at attractive margins. The model is replicable, the regulatory tailwinds are real and the market is large enough to sustain further consolidation.

Depth beats breadth in the facilities management industry

Focused, scalable business models with genuine density economics outperform diversified ones over time, by a wide margin. The temptation to add services and geographies is understandable in an industry where large contracts look attractive from the outside. But every incremental service line is also an incremental distraction. Peter Thiel has noted that you cannot run dozens of start-ups simultaneously and hope one works out. The same logic applies to a low-margin services business with finite capital and management bandwidth. Depth beats breadth, almost every time.

The FM industry is also at a genuine technology inflection. Advances in building sensors, AI-driven predictive maintenance and integrated data platforms are removing the ability of mediocre operators to hide. Buildings that were opaque are becoming transparent. Clients that once relied on SLA compliance reports are now demanding energy dashboards, asset-lifecycle forecasts and sustainability documentation.

Operators with weak processes and inconsistent data capture will be exposed. Operators with strong processes, standardised ways of working and an ability to translate data into value for customers will find themselves able to charge for something other than just labour. The buildings around us are getting smarter. The companies that service them need to be smarter too. The ones that are will be interesting to own.

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Korea is still an emerging market, or so MSCI reckons. On Tuesday, the most important provider of global indices – the MSCI World and the MSCI Emerging Markets matter much more than the equivalents from FTSE Russell and S&P Dow Jones – once again declined to put it on the watch list for upgrade to developed status.

On one hand, this situation feels increasingly ridiculous. Korea is a very advanced, high-tech economy, home to key tech players such as Samsung Electronics and SK Hynix. GDP per capita measured at purchasing power parity is higher than the UK, France, Japan and many other heavyweights. How can this be an emerging economy in any meaningful sense?

Yet there are aspects to Korea that feel like an emerging market. The ones that MSCI cites are certain limitations that bother institutional investors (restrictions on trading the Korean won offshore is a key one) – although FTSE Russell has classed Korea as developed since 2009, so the importance of these is not cut and dried.

However, perhaps more significant for the long-term future of the Korean stock market is the dominance of large business conglomerates (chaebols), of which the Samsung group is the biggest. The founding families of these groups still control them – often using a series of shareholdings between different listed entities – and frequently make decisions for their own benefit to the disadvantage of minority shareholders.

Generational changes are happening in Korea

Corporate governance is a major reason for the “Korean discount” – the fact that Korean stocks trade at lower valuations than peers elsewhere – but there are signs that this is changing. Policymakers have been pushing reforms, inspired by what governance changes in Japan have done for that market, with some success.

Generational changes also mean a structural shift in attitudes is inevitable, suggested a Korea manager at a recent conference. The individuals who built up chaebols in the 1960s and 1970s put huge importance on passing on control to their heirs as cheaply as possible (Korea has very high inheritance tax). They are now largely dead, the handovers are being completed, and tax bills are being settled. Their heirs will have different priorities that may often be better served by unlocking the full value of their businesses.

So the bull case for Korea sounds easy to make. It does not depend on MSCI one day acceding to the obvious, although being added to the developed index would result in significant inflows from tracker funds. And on the face of it, Korean stocks look very cheap – the MSCI Korea stock market index is on a forecast price/earnings ratio (p/e)of eight.

Yet this reflects the huge weight in Samsung and SK Hynix (65% combined) and how fast they are expected to grow. The MSCI Korea Equal Weight is on a forward p/e of 15, which is not cheap. Most of all, note the market is up by 260% in won terms in a year. If the AI boom continues, it will go higher, but have no illusions. Right now, a Korea stock market tracker is not a valuation play or a reform play – it is entirely an AI play.

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A new world calls for new stocks. In the VT De Lisle America Fund, we use the paradoxical combination of value plus momentum to find winners for the next decade. For 40 years, declining interest rates and disinflation created a powerful tailwind for steady growth stocks such as McDonald's, Nike and Procter & Gamble. Their predictability was rewarded with rising price-to-earnings (p/e) multiples, thus they strongly outperformed the market. That all changed in 2021 with the return of higher interest rates and inflation, combined with the launch in 2022 of ChatGPT, which funnelled capital into AI infrastructure.

Higher rates and inflation tend to push down p/e multiples and put pressure on profits due to rising costs of materials and labour. At the same time, the urgency to spend on building out AI pushed capital into different, previously unloved, parts of the economy: construction, manufacturing and blue-collar jobs. Investors like to find a comparison with past cycles. We think the 1970s provides the best precedent, but with the addition of AI. So how will that play out today?

Companies that own scarce real-world assets and have growing order backlogs gain pricing power in this new capital-expenditure-driven cycle, positioning them to thrive in the new industrial economy. Within these big macro themes, minor ones are also emerging. One we like is the break-up of old industrial conglomerates via “spin-offs” – the packaging of overlooked industrial assets into attractive new listed companies.

Three stocks for your portfolio

In 2025, Honeywell spun off its speciality chemicals division, Solstice Advanced Materials (Nasdaq: SOLS). Solstice holds an oligopolistic position in refrigerants (its cash cow, increasingly necessary for data-centre cooling) while expanding capacity in its specialist chemicals business, supplying America's semiconductor supply chain. But the hidden crown jewel is its stake in the only US uranium conversion facility – one of only seven in the world – and a scarce asset during a nuclear renaissance. Although expensive-looking at a high 20s p/e, its earnings power is underappreciated as its chip exposure grows and higher-priced uranium contracts begin to roll in.

Forum Energy Technologies (NYSE: FET) makes high-tech parts for oil wells and subsea exploration. It is a picks-and-shovels play on rising global energy needs due to AI and on the increasing complexity of extraction. Forum operates in a high-value niche and is a leading player in all its product lines. The company prides itself on its patented technical know-how, which makes it hard to compete against. Low reinvestment requirements also provide high levels of cash generation. Even after a near tripling over a year, we think Forum's stock is a buy given its cheapness relative to cash flow.

Demographic trends offer another type of steady growth. Pennant Group (Nasdaq: PNTG) owns, leases and operates care facilities for the elderly and sees the ageing population in the US as a steady tailwind to increase sales for years. Its ability to renovate old buildings to add value in a market where supply is constrained by the cost of new-builds is impressive. Growing demand and scarcer assets, plus entrepreneurial local management teams, are giving it the chance to execute its vision. Pennant trades on a low 20s p/e and has a high double-digit growth rate, giving it an enviable p/e to growth ratio of not much above one.

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Alphabet, Google's parent company, is listed in the US with a total value greater than that of the entire UK stock market. Billions of people use its search engine every day – indeed, the Google name has become so ubiquitous that it is now used as a verb around the globe. Yet there is more to Alphabet than Google.

Beyond search and advertising revenues lies an empire that includes everything from deep-sea cables to self-driving cars and energy storage. The business uses the billions harvested from search advertisements to fund massive bets on the future and is fast becoming one of the most influential companies in history.

The Alphabet name reflects a corporate mission to fund independent bets that produce “alpha” – the term in finance for an investment that outperforms the broader market. Alphabet wants to be the structure underpinning countless future innovations. The name signalled to the market that the firm was no longer just a search engine, but an incubator of new technology.

Alphabet's rise from Google search to global dominance

Search remains Alphabet's largest source of profits. Its enormous scale explains why the company can afford to fund so many broader ambitions. When the business launched from a garage in 1998, it was just one of many experimental search engines competing on the early World Wide Web. Its rapid rise to dominance was driven by a proprietary algorithm called PageRank. Unlike rival systems that mainly counted how often a keyword appeared on a page, Google ranked pages based on the quality and importance of links pointing towards them. A link from a respected university or major news site carried far more weight than one from an obscure blog. This breakthrough produced far more useful search results, triggering a wave of adoption that quickly led to dominance. Put simply, Google search worked much better than everything else.

Today, Google remains the search engine used by most. It controls more than 90% of the worldwide search market and processes billions of queries every day. Its closest rival, Microsoft's Bing, holds only a tiny share by comparison. Google's reach also extends far beyond its own homepage. The company provides the underlying search infrastructure for countless browsers and software applications around the world. Competitors struggle to replicate what Google has built because search engines improve through users' behaviour. The more people who use the platform, the more data it collects and the better the system becomes. By capturing most of the world's search data, Google continuously improves, creating a self-reinforcing cycle that keeps competitors behind.

This constant stream of searches is transformed into revenue through a system of paid results. When a user searches for a term with commercial value, the engine places sponsored links at the very top of the page, positioned directly above the information. Google avoids charging businesses a flat fee simply to display these links. Instead, it operates on a pay-per-click model, collecting a fee when a user selects a sponsored result. Because millions of consumers use the search box to find products, services and local businesses every second, these small fees accumulate into billions of dollars of highly predictable revenue.

This is so profitable because the underlying mechanics require little human involvement. Traditional advertising agencies only grow by hiring armies of account managers and media buyers to manage campaigns. Google removed much of this by building an automated, self-service advertising platform to run its pay-per-click business. Advertisers simply log into a dashboard, set their budgets and bid against one another for visibility tied to specific queries from users. Valuable searches, such as those related to legal or financial services, command extremely high advertising prices. This allows Google to generate enormous profits from everyday internet traffic without relying on large numbers of highly paid employees.

At the end of last year, Alphabet employed roughly 191,000 people worldwide. However, those workers are spread unevenly across the business. Most do not work directly on the core search or advertising operations. Instead, they are concentrated in labour-intensive divisions such as Google Cloud and areas such as compliance and other administration. The core systems and software that power Google's search engine require only a small group of engineers to maintain and monitor it. By the end of 2025, Alphabet was generating annual revenue equivalent to more than $2.1 million per employee, although the figure within search alone is probably far higher, perhaps as much as $10 million per employee. This ultra-low headcount relative to sales creates a self-operating engine that supports the rest of the organisation, funds Alphabet's broader ambitions and produces vast profits – thought to be $1 billion every two to three days.

Branching out into Google Cloud and beyond

The fastest-growing large-scale part of the business outside of search is Google Cloud. This division sells computing power and data storage to large corporations and public-sector organisations, providing a platform for businesses to build, host and run their own software applications. Unlike the search engine, the cloud business is inherently labour-intensive, requiring a global sales force. By the end of 2025, the unit had exceeded $70 billion in revenue, driven by demand for machine-learning applications. This segment spent years burning cash to build physical data centres, but has now matured into a highly profitable operation, generating billions in quarterly operating income. The third large division within Alphabet is subscriptions and devices. This includes premium, advertising-free access to YouTube, digital storage upgrades through Google One, which pools together personal consumer storage for Google Drive, Gmail and Google Photos. This is distinct from the corporate cloud, focusing instead on individual consumers' hardware, such as Pixel smartphones. Total consumers' subscriptions have climbed past 325 million globally. This division generates more than $50 billion annually.

What ultimately cements Alphabet's dominance is how seamlessly it intertwines these separate businesses. Google Video's early failure was solved by acquiring YouTube, for example, which was then deeply integrated into core search results. Google Maps was built to serve local search needs, but is now embedded directly into the Android operating system and Android Auto vehicles' dashboards. This interconnected web provides built-in, zero-cost marketing across the entire portfolio, making the user's experience smoother while locking consumers firmly inside Alphabet's systems.

The relentless flow of cash allows the parent company to invest on a scale few companies in history can match. Rather than returning profits to shareholders through dividends or share buybacks, Alphabet operates like a vast venture-capital fund. Its investment strategy is divided into three tiers. For near-term product improvements, it uses Google Labs, a fast-moving environment where software teams test early features, such as improved AI systems, directly with the public. For medium-term time horizons, the company focuses on strategic acquisitions, buying external platforms and scaling them over time. Finally, the long-term horizon is handled by X Development (formerly Google X), the “Moonshot Factory” created to back speculative technologies ranging from self-driving cars to grid-scale energy storage. In these ways, Alphabet channels its search, cloud and subscription revenues into tomorrow's cutting-edge technology.

Alphabet's formula for acquisitions

Alphabet has acquired more than 250 technology companies over the years. Each deal has followed a similar formula: acquire a promising but financially constrained technology and scale it using the company's engineering expertise and vast profits. Google Maps originated from Keyhole, a struggling start-up founded in 2001. Keyhole developed a 3D digital globe called EarthViewer 3D and even received early backing from America's Central Intelligence Agency. The technology was impressive, but the business model weak. Keyhole sold its software on physical CDs to real-estate firms and defence agencies. Google recognised that around a quarter of all web searches were location-related and acquired Keyhole in 2004 for roughly $35 million. It removed the expensive pricing, introduced a cleaner, more accessible interface, and relaunched the platform as Google Maps. In the process, it transformed a niche military-style tool into a free utility that has become almost as recognisable as the search engine itself.

The acquisition of YouTube in 2006 stemmed from Google's own failure in online video. Its in-house platform, Google Video, was losing ground to its rapidly growing rival. YouTube succeeded by offering a simple interface that allowed anyone to upload and stream videos easily. However, by the summer of 2006, the company was struggling under the weight of its own popularity. Hosting costs were soaring, while copyright lawsuits from traditional media companies threatened its survival. Realising Google Video had lost the battle, management stepped in with a $1.65 billion acquisition. The takeover rescued YouTube from likely insolvency and allowed Google to secure the leading destination for online video before legacy media companies could shut it down. By the end of 2025, YouTube was generating more than $40 billion in annual revenue.

The 2005 purchase of Android is probably the most successful acquisition. As a start-up, it had been developing an operating system for mobile handsets, but ran short of cash to fund engineering salaries. At the time of its purchase, it was a small company employing eight people and was bought for just $50 million. This was such a small sum at the time that it wasn't even disclosed to the stock market. The goal of the acquisition was to prevent competitors from blocking its search engine on mobile devices. By making Android free, Google rapidly came to dominate mobile software, eventually capturing more than 70% of the global smartphone market. This comparatively small investment helped ensure that the search business continued to grow even as smartphone usage overtook computer usage.

The 2014 acquisition of DeepMind secured Alphabet's lead in AI. The laboratory, which was founded in London by Demis Hassabis, Shane Legg, and Mustafa Suleyman, had assembled one of the world's strongest machine-learning research teams. DeepMind focused on neuroscience-inspired AI and deep reinforcement learning. Yet cutting-edge AI research is very expensive, requiring vast computing resources and highly paid engineers while producing little immediate revenue. Much of Hassabis's time was spent raising venture capital. Recognising that DeepMind needed the support of a company with deep pockets, the founders agreed to a £400 million sale to Google, with Hassabis taking on the role of CEO of the renamed Google DeepMind. The deal kept the research group based in London and provided the resources needed to pursue foundational scientific breakthroughs. That long-term backing ultimately paid off. Among other things, Hassabis's work on protein folding using DeepMind recently won the Nobel Prize in chemistry.

How Alphabet is shooting for the moon

Where Alphabet stands apart is its willingness to invest in technologies that may take decades to mature. The X Development division filters all ideas through a demanding three-part screening process to protect capital. Projects must address a global problem affecting millions, propose a radical breakthrough solution and rely completely on technology that does not yet exist. Incremental improvements are rejected outright. To encourage bold experimentation, X is also designed to reward failure. Teams are expected rigorously to test their ideas and can even receive bonuses for proving a project is technically or economically unworkable before significant resources are wasted.

This strategy has produced a trail of discarded technologies, including mysterious, giant floating barges intended to be high-end, floating marketing showrooms; a technology for storing renewable energy by pumping electricity into massive tanks of molten salt and chilled liquid; high-altitude, helium-filled balloons designed to float in the stratosphere, creating a shifting network to beam wireless internet down to remote rural communities. But the crown jewel of the moonshots to date is Waymo, the autonomous-vehicle division that began life in 2009. Waymo shows how a massive cash cushion allows a company to outlast an industry cycle. While some car makers promised self-driving fleets by 2018 only to scale back their ambitions when machine learning proved too difficult, Alphabet simply maintained its multi-billion-dollar funding trajectory. By refusing to rush out unproven systems to market, the division solved the major challenges.

Waymo has now achieved scale, with roughly 3,700 vehicles operating, servicing half a million paid rides per week. Its fleets of autonomous vehicles operate robotaxi networks across major American cities, including Phoenix, San Francisco and Los Angeles, completing passengers' trips without human drivers. In September of this year, it is due to launch in London. What began as a highly speculative experiment has matured into a genuine advancement in transportation.

Deep underwater, Alphabet is also building global subsea cable infrastructure. This is an ongoing project that has so far created a total of 60,000 miles of armoured cabling crisscrossing the oceans. To support the growth of its cloud services and advertising, Alphabet shifted from renting space on third-party telecommunications networks to owning its own. These subsea lines are the plumbing of the internet, moving vast amounts of data across the world at the speed of light. In owning this infrastructure itself, Alphabet ensures its consumer services operate with lower latency than that of competitors.

Is Alphabet worth owning?

Turning digital advertising revenue into real-world infrastructure requires enormous investment. For investors, the key question is whether these assets will create lasting value or simply become an expensive distraction. The shares of Alphabet rarely look cheap on any conventional valuation metric, but waiting for a deep-value entry point has been a fool's errand. Ever since the company listed on the stock market in 2004, there has never really been a bad time to buy its shares.

Not that the shares have risen consistently. Alphabet's shares have fallen quite significantly a few times over the years, dropping roughly 50% during the 2008 financial crisis and weathering several 20%-30% declines since. Every single decline has proved to be an exceptional buying opportunity, as the underlying earnings have moved relentlessly higher. This compounding has generated astonishing wealth, transforming its founders into centi-billionaires and ranking them among the wealthiest individuals on Earth. The model does not just reward senior executives. In 1999, when Google employed just 40 people, massage therapist Bonnie Brown joined the company part-time. Her pay was only $450 a week, but she also received stock options. Five years later, she retired a multi-millionaire and went on to create her own charitable foundation. Had she kept her shares, she would now be a billionaire.

Despite a massive market valuation of about $4.5 trillion, Alphabet is still growing remarkably quickly. A simple heuristic for evaluating growing companies is to ask whether the business can generate enough operating profit within five years to make its current enterprise value look cheap. Specifically, can its future operating profits reach a tenth of that valuation? For Alphabet, that means aiming for roughly $450 billion in annual operating profit. Last year it made about $190 billion and is forecast to grow at 20%-25% per annum for the next five years. At that level of growth, the company's current trajectory makes $450 billion perfectly feasible.

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Private debt went through a “golden moment” after the rapid post-pandemic rise in interest rates, said Jonathan Gray, president of alternative-asset giant Blackstone, in 2023. The question now is whether that golden moment is past. With interest rates expected to stay higher for longer, sovereign yields rising sharply, and cracks appearing last summer in US business development companies (BDCs), some investors wonder whether private debt is entering its first real test as an asset class – or even facing a day of reckoning.

Private debt is a broad label. It includes syndicated leveraged loans, direct lending, asset-backed finance and even fund financing. These distinctions matter. Syndicated loans are liquid and volatile, but trade at tighter yield spreads (ie, they promise lower returns). By contrast, direct lending – where investors such as funds lend directly to borrowers – is illiquid and assets are rarely marked to market.

Direct lending is often presented as the core of “true” private debt, due to its potential for higher risk-adjusted returns. So far, that record has proved hard to ignore for institutional investors. Spreads of around 550 basis points over base rates remain appealing, while reported default rates are still modest. As a result, it attracted large inflows from pension funds and insurers. Assets could reach $2.8 trillion by 2028, up from $1.8 trillion currently, according to private-markets data firm Preqin.

However, this influx of capital and its potential ability to skew industry fundamentals has meant that some participants and regulators have begun to voice concerns about the risks of a private-credit crisis. Some signs of stress have emerged. US BDCs made the headlines last year after a rise in the number of investors who tried to redeem their holdings. Open-ended funds that invest in illiquid assets can enter a vicious cycle when redemption requests rise: as funds sell their most liquid assets (often assets of better quality) to meet redemptions, that news creates an incentive for other investors to also redeem so as not to be the ultimate “bagholders” of the riskiest and less liquid assets. In order to avoid the proverbial rush for the exits, some BDCs were obliged to cap redemptions – which obviously does not improve investors' sentiment.

A more challenging macro-economic environment, slower growth, persistent inflation and rates that are higher for longer also raises the risk that the asset class could be entering a more difficult phase. A further concern for investors trying to understand these risks is that valuations are opaque and largely controlled by managers. However, as the asset class is becoming more institutionalised, index providers such as S&P and Bloomberg are developing private credit benchmarks. Along with BlackRock's acquisition of Preqin in 2024, this suggests private markets will become more standardised and scrutinised despite some fund managers fighting this trend.

Private debt may like high interest rates, but borrowers don't

However, the primary concern at present is that the same high interest-rate environment that makes private debt attractive to investors is also increasing pressure on borrowers. The probability of default is growing, while recovery rates in private debt have never really been measured. Defaults can be obscured: for example, the restructuring of US educational technology firm Anthology last year did not trigger a formal default, as its lenders allowed flexibility in payments. Payment-in-kind (PIK) – where interest is added to the loan principal to be paid at maturity – can similarly mask stress by deferring payments out of cash flow. The covenant-lite nature of some lending offers less protection than investors might expect, while recovery rates in restructurings may be weaker than for senior debt that requires regular repayments in cash.

Meanwhile, diversification in some private-credit vehicles looks weaker than it first appears. A significant share of portfolios are exposed to software and/or software-as-a-service (SaaS) businesses, creating hidden concentration risk. These companies benefit from recurring revenues, predictable cash flows and healthy earnings before interest, tax, depreciation and amortisation (Ebitda) margins, but there are fears that artificial intelligence (AI) fundamentally threatens their business models. AI may not disrupt these companies overnight, but it could gradually erode pricing power, compress margins and weaken exit valuations, making refinancing more difficult.

The sell-off in these software stocks earlier this year, combined with the impact on private debt as investors realise how exposed some lenders are to the sector, has highlighted hidden correlation risks in supposedly diversified portfolios. All lenders now have their eyes on business-software firm Visma, which has reportedly delayed its planned initial public offering (IPO) until 2027 – a decision that perhaps suggests growing caution among investors despite strong operations and cash generation. This highlights another important feature of the market: concentration in a small number of large credits backed by private-equity sponsors. Jitters in private debt can – by definition – be less publicly visible, but the performance of HgCapital Trust, the specialist private-equity investor in software and services that has 13% of its portfolio in Visma, testifies to how sentiment has changed: it is now trading at a 25% discount to net asset value (NAV), having been on a premium in 2024.

Momentum remains in the private debt market

And yet, the market remains active. Despite slower mergers and acquisitions (M&A) activity in Europe during the first quarter, two large refinancings – of TK Elevator (€1.8 billion) and Global Sports Group (€2.2 billion) – drove solid deal volumes. “The prominence of these large-cap deals also suggests direct lenders have successfully taken advantage of the volatility seen in Q1 to reclaim some market share from the syndicated markets,” notes Debtwire. The amount of funds raised in 2022-2024 that are not yet invested (known as “dry powder” in the industry) will allow the market to keep momentum.

The fact that direct lending can offer 100-500 basis points of additional yield over what is available in the traditional syndicated loan market (depending on the amount of leverage used by the vehicle, or if it acquires subordinated debt and junior capital) – combined with the ability to negotiate better structural protections than broadly syndicated loans – should continue to attract strong interest.

Dry powder will help lenders to inject capital if needed and protect their initial investments, tempering the risk of a private-debt crisis. It will be used to address the “refinancing wall”: a large stock of debt raised in the low-rate era now needs to be rolled over at significantly higher cost. So far, this has been managed through extensions and amendments – euphemistically renamed as Liability Management Exercises (LMEs). Widespread defaults are rare.

We also need to keep in mind that there are important regional differences in private debt. The US market is more mature and increasingly competitive as banks re-enter leveraged finance, given an incentive by the Trump administration's new regulations. In Europe, private debt is still expanding, supported by a more fragmented banking system and structurally lower penetration. Note too that public markets are treating private credit as a homogeneous bet on leveraged buyouts. However, outcomes will depend less on the asset class itself and more on managers' capabilities: origination, underwriting discipline and balance-sheet flexibility. Scale is an advantage in stressed environments. Large managers such as Ares, Apollo and Blackstone have the ability to amend loans, provide follow-on capital and manage restructurings internally. Origination is the real moat, because it separates lenders that focus on financing commoditised leverage buyouts (LBOs), which are often syndicated loans, from those that source bilateral or semi-bilateral deals with pricing power and better protections. Collateralised loan obligations (CLOs) – securities backed by a pool of loans, often from LBOs – have held up so far and offer diversified exposure to leveraged loans. However, their lack of control over the underlying loans and consequently over the outcomes when borrowers come under pressure may become more apparent as the cycle turns.

The easy part – that “golden moment” – is over. Higher rates are a source of stress. As refinancing pressures build and dispersion rises, returns will be less a function of a rising tide lifting the whole asset class and more driven by selection, discipline, structure and scale. A broad opportunity is turning into a more challenging game.

High-performing private-debt funds generally require high minimum commitments (ie, institutional size – maybe €2 million - €5 million to a private-debt fund such as CVI with strong exposure to central Europe). Some managers are starting to target individual investors as a source of further capital, but one should always be aware that individuals are less likely to get the best opportunities. Avoid products offered by private banks where layers of fees accumulate.

More interesting are listed funds and managers exposed to the sector. Some merit caution, but fears of a crisis may create buying opportunities in the best ones. In Europe, there is Tikehau Capital (Paris: TKO), which has robust exposure to special situations, ICG (LSE: ICG) and CVC Income & Growth (LSE: CVCG). In the US, Ares Management (NYSE: ARES) and Blackstone (NYSE: BX) have developed the strongest platforms in terms of origination. Apollo Global Management (NYSE: APO) has the strongest exposure to direct lending, but readers may prefer to wait for the dust to settle.

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RentGuarantor Holdings (Aim: RGG) has been given a boost by the Renters' Rights Act, one of the most significant pieces of legislation to hit the UK rental market in decades. It's only been in force since the beginning of May, but the Act is already driving a complete rewriting of the market.

Under the new law, fixed-term tenancies have been abolished, “no fault” evictions are no longer allowed, rents can only be raised once a year, and during the first 12 months of the tenancy, the landlord cannot serve notice to move back into the property or sell it. These changes, far from protecting tenants, have forced landlords to become more defensive.

The changes have made it much harder for landlords to evict tenants who can't or won't pay their rent, piling pressure on a system that's already on the verge of collapse. According to professional body Propertymark, due to lengthy court backlogs, the average time from claim to repossession has risen to more than 68 weeks, compared with just over 20 weeks in 2019. At the point of eviction, average unpaid rent stands at £12,708 across England and Wales and £19,223 in London.

Landlords have responded by demanding that tenants provide a guarantor before they agree deals. According to multiple reports, around 40% of landlords now require guarantors for both new and existing tenants. This is where RentGuarantor comes into play.

How RentGuarantor works

The firm is a rare example of how effective London's capital markets can be for early-stage growth businesses. Founded in 2016 by Paul Foy, a property investor since the mid-1980s, RentGuarantor does what it says on the tin – guarantees rents. Tenants pay a fee (£20) for an initial background check and the firm uses tools such as Open Banking and AI to calculate how much the tenant can afford and if they're able to maintain payments. If the tenant passes the check, which should be completed the same day, RentGuarantor can offer the guarantee.

This incurs a further fee, usually around three to five weeks' rent, depending on the underlying risk profile. When the tenant has paid and signed, RentGuarantor provides a legally binding guarantee of rental payments to the landlord or letting agent. Unlike traditional guarantors, such as parents or grandparents, this provides an extra layer of protection for the landlord. RentGuarantor passes the risk to a panel of insurers while collecting the origination fee and remaining the key point of contact for customers.

Five years of RentGuarantor Holdings on the London market

After spending five years building the foundations, Foy and his team took the company public in 2021. It listed on the Aquis exchange in 2021 with hardly any revenue and moved to the Aim junior market in the second half of 2025. The new listing raised £4 million in 2025 to support its growth efforts and it ended the year with revenue of £2.4 million, up 87% year-on-year. The founder has remained a key shareholder with a 30% stake.

RentGuarantor hasn't charged into the market seeking break-neck growth and drawing down shareholders' goodwill to fund spending. There's a very tight grip on marketing spending, which totalled just £200,000 in 2024 and £500,000 in 2025 against revenue of £2.4 million, or around £165 per contract (based on the year-end figure of 3,123 contracts). The focus over the past five years has been on getting the offering right and putting in place the right technology and team to scale up effectively.

The firm has now reached the point where this hard work is beginning to pay off. In May, the month the Renters' Rights Act came into force, RentGuarantor recorded a 115% increase in unaudited revenue compared with the average for the first four months of the year. Moreover, revenue per contract was up 24%. The group also recorded its first positive monthly Ebitda earnings since its admission to trading – well ahead of the board's expectations.

The challenges facing RentGuarantor Holdings

The key risk for the group here will be scaling up without falling flat on its face, as so many firms do when they encounter a sudden surge in demand. The Act is driving demand for guarantees, but it'll also lead to a surge in disputes.

To help, RentGuarantor is looking to AI and has an expert on the matter in its orbit. The AI strategy is being led by Dave Cliff, a non-executive director and professor of computer science at the University of Bristol. He previously worked at MIT's artificial intelligence laboratory, so unlike many other businesses, which seem to be turning to AI with little actual understanding of the benefits, drawbacks and costs, RentGuarantor looks well-placed to exploit the benefits of the technology fully. Management estimates the group can process 20,000 contracts per year, but that will rise to 100,000 with AI's help.

According to house broker Shore Capital, RentGuarantor could agree 7,000 contracts this year, 13,000 in 2027 and 62,000 by 2030. Revenue could hit £6 million in 2026, rising to £19 million by 2028 and £54 million by 2030. Even if it achieves this lofty growth, it would still leave the group at only 3.4% of the potential total market.

Now that the firm is essentially self-funding, there's scope for marketing spending to rise. Shore Capital expects a ten times rise by 2030, easily covered by the firm's 79% gross margin. The broker has pencilled in adjusted earnings per share of 3.6p by 2028. As with all early-stage firms, these forecasts are likely to be wrong, but they illustrate the growth potential if the firm manages to scale up over the next 12 months. This is a high-risk play, but one with a huge and growing market to support it.

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The emerging market (EM) universe is very diverse in terms of what drives individual economies. What does China have in common with India (other than being populous and in Asia) or either of them with Brazil? Yet they are treated as a block, and recent trends are stretching these contradictions further than ever.

A top-down investing strategy often involves assigning things to groups, then buying the most compelling groups or choosing the most attractive within a group. These groups can seem arbitrary – the difference between members can be as big as the similarities. Yet in the investment business, classifications that seem easy to understand can stick around well past the point where they make sense.

Standard rules of thumb for emerging markets would tell you that the last few months have been difficult. Many emerging markets are energy importers, so will suffer from higher oil prices. Markets also tend to be affected by inflows and outflows from foreign investors. If global investors get more nervous, they would be expected to cut emerging-market exposure first and take their money home. Yet the MSCI Emerging Markets index is up by 20% in sterling so far this year. How?

AI stocks are over-represented in emerging markets indices

The explanation hinges on two points. The first is that two of the biggest markets in the index are emerging markets only in one very specific sense. South Korea and Taiwan retain certain restrictions, mostly around their currencies, that MSCI deems incompatible with being in the developed markets group. Yet in many respects, they are both wealthier and more advanced than many developed economies.

The second is that a few huge companies – Taiwan Semiconductor (TSMC), Samsung Electronics, SK Hynix – are huge beneficiaries of the AI boom and are driving their markets even more than the Magnificent Seven drives the US market. Those three stocks account for almost 30% of the MSCI Emerging Markets index. Taiwan and Korea together make up 50% of the index. In turn, TSMC is 55% of the MSCI Taiwan, while Samsung Electronics and SK Hynix account for 60% of the MSCI Korea.

These are eyebrow-raising numbers. They have worked out very well for any broad emerging-market investor. Still, we must remember that if the AI boom ends and the US market slumps, the emerging market index will do the same – it's been a play on the same theme.

If you want diversification, you will only find it in funds whose mandate does not bring in these stocks – BlackRock Frontiers (LSE: BRFI) or Barings Emerging EMEA Opportunities (LSE: BEMO), for example. Of course, these funds have lagged in recent months, held back by the lack of tech exposure or battered by the Middle East crisis. I would not say it is yet time to rotate out of broader emerging market funds. But it is something to keep in mind if the crisis passes and the AI boom falters.

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Helium is a commodity that is key to every major growth theme in the global economy – space, AI, and healthcare. But almost nobody talks about it – and the helium supply picture has just become dramatically more complicated.

The launch of a single Falcon 9 rocket consumes roughly 14%-18% of the world's daily helium production in a single ignition sequence. SpaceX launches Falcon 9 rockets dozens of times a year, with ambitions that stretch well beyond that frequency. The satellite industry is preparing for annual launch volumes of between 3,700 and 5,000 by 2030, as mega-constellations reach full deployment. Goldman Sachs anticipates 70,000 low Earth orbit (the region between 160 and 2,000 kilometres into space) satellite launches globally between 2025 and 2031. Every single one of them needs helium. There is no alternative.

So surely someone is producing more of it? They are not, at least not at anything close to the rate the market requires. Helium is not manufactured. It is extracted as a by-product of natural-gas processing in a small number of locations where underground concentrations happen to be commercially viable. The US and Qatar together account for more than 75% of global supply. Russia produces a significant share, but that supply is unavailable to Western markets. Algeria contributes a modest fraction. Everyone else is a rounding error.

Qatar's share, 30% of global supply, flows out of a single industrial complex at Ras Laffan. In March 2026, Iranian strikes forced QatarEnergy to cease production of liquefied natural gas (LNG) and associated products, including helium. Almost one-third of the world's helium supply was removed from the market overnight. Spot prices doubled. The south site at Ras Laffan took direct hits and will not restart before late summer 2026. Permanent capacity reductions, analysts say, will take years to recover fully.

The Strait of Hormuz is a trigger, not the underlying problem. Even before the first missile flew, this market had endured four recognised major shortages over the past two decades, each lasting two to three years before any equilibrium was restored. The conflict simply made the market's structural deficit visible. Compounding the supply picture is the nature of helium itself. It is the second-lightest gas on Earth. It escapes containment at a rate that makes strategic stockpiling impossible. You cannot build a meaningful reserve. When supply breaks, the market has no buffer.

Now consider who is competing for that inelastic pool of supply. Semiconductor makers use helium at nearly every stage of wafer production, and there is no substitute for its role in extreme ultraviolet (EUV) lithography, the process that makes the most advanced AI chips. The AI-driven chip market is set to double by 2030 at a compound annual growth rate above 11%. MRI machines make up 20% of the global demand for helium, each requiring an initial fill of 2,000 litres of liquid helium and continuous top-ups throughout their operational life.

As India and other large emerging markets rapidly expand healthcare infrastructure, that demand grows structurally. And then there is the quantum-computing sector, scaling fast and entirely dependent on liquid helium cooling to reach the cryogenic temperatures that make quantum processors function at all.

Rocketry, AI chips, medical imaging, and quantum computing. The three or four fastest-growing sectors in the global economy all compete for the same gas from the same small group of producers, and one of those producers has just been taken off the board for an indeterminate period.

The best helium stocks to buy now

Investors should note that SpaceX's S-1 registration statement, filed ahead of what promises to be one of the most significant listings in a generation, conspicuously omits any reference to risk associated with helium – even though the company has already acknowledged, through its own CEO, that helium supply represents a binding operational constraint on its ambitions to grow. Elon Musk stated plainly that there is not enough helium produced on Earth to sustain a high-flight-rate Starship programme, a constraint significant enough that the vehicle had to be redesigned around it. That is not a footnote. That is a material operational risk.

Consider instead the industrial gas companies Linde (Nasdaq: LIN), Air Products & Chemicals (NYSE: APD) and Air Liquide (Paris: AI), the obvious primary beneficiaries of tighter supply and rising prices, with pricing power that will compound through long-term supply contracts. The UK angle deserves particular attention. Britain has no domestic helium production, no strategic reserve, and no formal critical-minerals designation for helium by the government. The NHS scanner estate, the National Quantum Computing Centre at Harwell and the defence-electronics supply chain are all exposed to a commodity that receives no policy attention in Whitehall. That is a gap waiting to be filled, and investors who identify it before policymakers do will have done so at the right time.

Helium has been treated as background infrastructure for too long, considered too cheap, too abundant, too boring to warrant serious analysis. That era is over. The commodity no one talks about is the one underpinning the launches everyone is watching, the chips powering the AI everyone is funding, and the scanners keeping hospitals operational. The question for investors is not whether helium matters. The question is how long the rest of the market takes to realise it.

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Anthropic submitted a draft registration statement to the US regulator on 1 June for its imminent initial public offering (IPO), the second US technology company to do so in recent weeks.

Slipstreaming SpaceX (whose own IPO is expected later this month), the San Francisco-based artificial intelligence (AI) company behind the Claude series of large language models (LLMs) said the amount it was targeting – determined by the number of shares to be issued and their price – had not yet been set.

An unattributed statement on its website said: “Today, Anthropic, PBC confidentially submitted a draft registration statement on Form S-1 to the U.S. Securities and Exchange Commission for a proposed initial public offering of our common stock. This gives us the option to go public after the SEC completes its review. The proposed initial public offering will depend on market conditions and other factors.”

The company has appointed Morgan Stanley and Goldman Sachs to lead its listing process, according to Bloomberg, which said J.P. Morgan was also involved.

The flotation is expected to take place as soon as October, although many details are still speculative.

Which fund managers have invested in Anthropic?

Just days before it confirmed submitting its paperwork to the SEC, Anthropic announced it raised $65 billion in a series H round, led by Altimeter Capital, Dragoneer, Greenoaks and Sequoia Capital, bringing the company’s estimated valuation to $965 billion.

Brad Gerstner, founder and chief executive of Altimeter Capital said: “Claude’s latest advancements have driven large-scale adoption among the world’s most demanding organisations. This momentum positions Anthropic to lead the next phase of AI innovation and capture the enormous opportunity ahead.”

Co-leading the round were Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ and XN. Other “significant investors” named included Baillie Gifford, Blackstone and T. Rowe Price.

The raise also includes $15 billion of previously committed investments from hyperscalers, including $5 billion from Amazon.

What is the easiest way for UK retail investors to hold Anthropic?

Several investment trusts hold Anthropic, allowing investors exposure to the stock without them having to get involved in the often onerous and volatile IPO process.

Annabel Brodie-Smith, communications director of the Association of Investment Companies (AIC), said as it’s easier for investment trusts to hold privately held companies, these are a sensible option for DIY investors.

Five investment trusts have exposure to Anthropic, which she said “provide retail investors with a way of getting exposure before the crowds pile in when the company is listed on the stock market”.

Source: AIC / Morningstar and investment trust managers (as at 02/06/2026 based on latest available published portfolio weights).

What are Anthropic’s growth plans?

The fundraising announcement also detailed recent expansion of its compute capacity, including signed agreements with Amazon, Google, Broadcom and SpaceX. It said Claude was the first frontier model available on the three largest cloud platforms, Amazon Web Services (AWS), Google Cloud and Microsoft Azure, with AWS its main cloud provider and training partner.

Alfred Lin, partner at Sequoia Capital said: “Startups and Global 5000 companies alike are deploying Claude to handle complex workflows, and in doing so, Claude is learning how businesses actually operate: the context, the processes, the judgement. Anthropic is building the bridge between where enterprise AI stands today and where it’s headed.”

Since its series G round in February, the company said adoption has grown across global enterprise customers and its run-rate revenue (a company’s estimated annual revenue based on a multiplier of a short-term, indicative period) crossed $47 billion.

As a public benefit corporation (PBC) Anthropic is a for-profit company that prioritises its purpose of “the responsible development and maintenance of advanced AI for the long-term benefit of humanity”.

While not yet confirmed, as a high-profile tech company, the stock is expected to list on the Nasdaq exchange. These recent announcements suggest it has now overtaken its rival OpenAI in the race to go public, allowing it to exploit surging investor demand for all things AI.

Anthropic, OpenAI and SpaceX are being touted as the three landmark listings set to take place in 2026 that are changing the playbook for IPOs, including how index providers are facilitating their inclusion in benchmark indices.

Ceres Power Holdings (LSE: CWR) is one of many companies to have recently got caught up in the global AI boom. Shares in the fuel-cell provider have charged higher by 240% year-to-date. Over the past 12 months, the shares have risen 850%. Despite this performance, the stock is still down around 50% from its ten-year high in February 2021.

UK-based Ceres Power is a developer of solid oxide fuel cells (essentially mini power stations) and hydrogen-power technologies. For many years, the company and its technology were relatively unloved due to high costs and low demand. That has changed over the past 12 months thanks to the massive energy demands of AI, leading to what can only be described as an arms race for power. Data-centre operators and the so-called hyperscalers – Alphabet, Microsoft, Amazon and Meta – are seeking their own power sources as capacity-constrained electricity grids are unable to meet their needs.

Electricity demand from data centres soared by 17% in 2025. The power demand from the average newbuild data centre is forecast to rise to almost 110MW by 2030, from almost 47MW in 2025, according to S&P Global. Globally, data centres could consume 1,000 terawatt-hours (1,000,000GWh) of electricity by 2023, up 100% from 2030.

In November 2024, US utility American Electric Power entered into a landmark supply agreement with Bloom Energy to procure solid-oxide fuel-cell products capable of delivering 1GW of power. Designed to plug directly into AI data centres, the fuel cells can run on natural gas, biogas or hydrogen blends and, most importantly, can be delivered and turned on in months, not years. Data-centre company EdgeCloudLink claims it can construct a data centre and have it running within nine months, partly thanks to fuel cells removing dependency on power utilities.

A turnaround for Ceres Power?

The market seems split on whether Ceres can replicate the success of its US peer. Its record of delivering is spotty to say the least – revenue hasn't grown over the past five years. It is holding out on its next-generation Endura technology, a solid-oxide stack platform that can run on both natural gas and hydrogen. A solid-oxide stack uses ceramic electrolytes to convert fuels into electricity, and Ceres claims its technology can do so more efficiently than its competitors.

At scale, manufacturing costs are expected to be one-third lower than that of its competitors, according to Ceres, and its output aligns perfectly with the electrical requirements and standards of modern data centres. Berenberg analysts describe this as a “gamechanger” that will allow the company to monetise its research and development into a scalable platform.

Peel Hunt analysts believe this is nothing more than a branding exercise, repacking the company's existing technology into a new product. But ultimately, the company's success will depend on its ability to sell licences for its products. Over the past few years, Ceres has transitioned away from a manufacturing model to a licensing model and has outlined a goal of securing at least one new manufacturing licence agreement per year. That doesn't look like a particularly high bar considering the company has identified a 22GW market opportunity for its products by 2030, driven by demand from industry and data centres, particularly in Asia and the Americas.

A single partner scaling up to 1GW of production using Ceres' new Endura technology could generate £50 million to £100 million in annual royalty revenue. Berenberg believes that would generate $1 billion in shareholder value at current sector valuation multiples. Compared to Ceres's current market capitalisation of £1.4 billion, it's easy to see why investors have raced into the stock.

Should you invest in Ceres Power?

The next few years will be key. Analysts have pencilled in revenue of around £80 million for 2028, up from £52 million in 2024 when the company started its transition to a licensing model. This isn't enough to justify the current valuation. Still, these figures were compiled before the company announced a partnership with Centrica (the owner of British Gas) and Delta Electronics (a Ceres manufacturing partner) for off-grid energy generation.

The partnership will offer customers “competitively priced, on-site power generation, significantly reducing exposure to wholesale electricity market volatility and grid capacity constraints”. The plan is to deploy a demonstration site within the next 12 months and scale up capacity over the next three to five years. Other partnerships signed in 2025 are expected to ramp up and start delivering results in 2026, including partnerships with Shell in India, Doosan in South Korea and Weichai in China.

Five years is a long time. The firm is still loss-making when measured by Ebitda and is burning through cash (Ebitda of £7.8 million is projected for December 2028). The shares are trading at 17.5 times forward sales. Still, with £83 million of cash in the bank at the end of 2025, Ceres has the resources to sustain itself for the next three years until it reaches break-even point. The company burned £20 million of cash in 2025 and costs are expected to be down by around 20% this year.

Ultimately, Ceres is a high-risk play and the company's valuation does not leave much room for error if sales fall below expectations next year. However, it's clear there's a large and growing market for the fuel-cell technology Ceres has spent years developing. With 50GW of additional electric supply needed in the UK alone to meet demand from AI data-centre projects in the pipeline, even a relatively small order could transform the company's fortunes.

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By European stock market standards, the size of the SpaceX initial public offering (IPO) will be breathtaking. The company is expected to be valued at between $1.75 trillion and $2 trillion, and given how frothy Wall Street is right now, it would hardly be a surprise if it went to a substantial premium on its first few days of trading. We can all question the valuation. The Starlink business that now provides internet access on flights is a clear money-spinner and it may be able to break into domestic broadband as well, but the plans for a colony on Mars look, to put it politely, a little optimistic. Even so, this is a huge business and a very successful one, and it has created a huge amount of value in a very short period of time.

It is far from alone. Anthropic, the company behind Claude AI, is reported to be planning an IPO in October, with a valuation of $1 trillion or perhaps more. Its rival OpenAI, the company behind ChatGPT, is also expected to list later this year, with a value of close to $1 trillion. There are slightly smaller companies just behind it. Last week, Cerebras, which makes AI chips, made its debut on Nasdaq, and after a first-day premium, saw its value soar to $95 billion. On the US market, incredible amounts of wealth are being created at dizzying speed. Anthropic is only five years old, OpenAI is ten (its profit-making unit only five) and although SpaceX was founded in 2002, it only really got going a decade ago.

The contrast with European stock markets is painful. SpaceX by itself will be worth almost as much as the whole of France's CAC-40 (valued at €2.6 trillion and falling rapidly as the value of LVMH slumps). It will be getting close to the entire value of Britain's FTSE 100, currently valued at £2.4 trillion, and SpaceX and Anthropic combined will certainly be worth more than all of the UK's 100 largest companies put together.

European stock markets need more mavericks like Elon Musk

The reason is clear. Very few new firms are being created. If you exclude mergers, the newest company on the CAC-40 is Eurofins Scientific, which was formed in 1987. Even where there are new companies, the best ones choose to list on Wall Street – the Cambridge-based chip designer ARM, for example, is now worth $220 billion, which would rank it as the third largest in the FTSE 100 if it had decided to list here.

Europe, including the UK, needs to realise how far behind it has fallen and start working out how to turn that around. First, it should radically reduce the taxes on start-ups to encourage more entrepreneurs. Britain has scaled back the break on capital-gains tax that anyone who started a new company used to benefit from, and most of Europe never had any concessions to start with. Instead, there is a constant stream of new wealth taxes and capital-gains taxes, with the Netherlands extraordinarily planning to tax capital gains before they have even been cashed in. No wonder there are far fewer start-ups and hence fewer giants ever emerge.

European stock markets should also roll back restrictions on growth industries such as AI and space. While the US has a booming space industry, Europe has a Space Act; while huge new AI businesses are created on the other side of the Atlantic, Europe is stuck with an AI Act. But there is no point in having a regulator if there isn't an industry to make rules for. There is still little sign that politicians in either Brussels or London realise how much damage has been done by trying to regulate industries before they have even begun.

Finally, Europe should relax the listing rule for entrepreneurs such as Elon Musk who want to keep control of companies. SpaceX will come in for a lot of criticism for allowing Musk so much control over the business and the $1 trillion pay package if he manages to create a thriving human colony on Mars. It doesn't follow Europe's governance rules. But so what? Entrepreneurs are often a little odd, and they are often control freaks, but they also have the drive and ambition to create huge new businesses. Europe could use fewer rules and more mavericks if it is to avoid turning into an investment backwater, with nothing more than a dull collection of very old companies.

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What force will shape the world in the next 20 years? The answer is China's drive to financialise, according to Diana Choyleva, founder and chief economist at Enodo Economics.

In this episode of the podcast, Diana speaks to MoneyWeek's Cris Sholto Heaton about how the AI race differs in China versus the West, the transformation of the country's equity market, and the breakdown of globalisation.

You can watch this episode on our YouTube channel or subscribe to it on any podcast platform.

About the podcast

MoneyWeek Talks is a podcast that helps you unlock the secrets to financial success. Editors Kalpana Fitzpatrick and Andrew Van Sickle are joined by influential guests – from CEOs and entrepreneurs to economists and policymakers – to share their top tips on managing money, investing wisely and building wealth.

Subscribe to the MoneyWeek Talks podcast and get ready to make it, keep it and spend it with confidence.

In February, major US brokers such as Marsh & McLennan , Willis Towers Watson, Aon and Arthur J. Gallagher & Co. declined by 8%-11% in a single day on news that OpenAI, the owner of ChatGPT, had approved the first insurance-focused AI app designed by US intermediary Insurify. OpenAI's tool arrived a week after Claude, the model developed by Anthropic, also released a new plug-in to automate sales, legal and financial analytical functions.

As well as this risk of obsolescence, investors have had to try to factor in the growing challenges of a so-called “soft” insurance market. Since 2017, the insurance market has been in a “hard” phase, where prices have been rising, and profits have jumped. However, two years ago, prices started to flatten and then fall as the market turned from hard to soft. The hard market was very good to Marsh & McLennan (NYSE: MRSH). Between 2017 and the beginning of 2024, shares in the broker and global-intelligence company rose more than 200%, but since topping out in the first half of 2025, they have fallen by around 28%.

This decline was needed. Insurance is a highly cyclical business and, coming into the soft cycle, Marsh was trading at about 22 times forward earnings, a multiple that left little, if any, room for error. After the re-rating, the shares are now trading at just 16.8 times forward earnings, according to UBS. That is still a bit high for this stage of the market cycle, but there's a good argument that you should start buying the shares at this level.

Marsh & McLennan plays an important role in the insurance market

Marsh & McLennan is the parent firm of Marsh Inc, one of the world's largest risk-management and insurance-services firms. The group also owns Guy Carpenter, a risk-management and reinsurance specialist; management consultancies Mercer, plus Oliver Wyman and Jardine Lloyd Thompson Group (JLT), an insurance, reinsurance and employee-benefits broker based in London.

The group's largest division is Marsh Risk, which generated $14.4 billion in revenue in 2025. The second largest is Mercer, with revenue of $6.2 billion, and Marsh Management Consulting, at $3.6 billion. The total consulting business turns over $9.8 billion a year. The risk-management and insurance businesses (including Marsh Risk) generated $17.3 billion in revenue.

Marsh Risk plays an important role in the insurance market. Large, complex risks are often underwritten by pools of insurers and reinsurers bought together by brokers. The insurers like it because they're not overly exposed to a single risk, and the buyer of insurance likes the security of multiple parties underpinning the contract. Marsh Risk helps navigate this process. The company also manages the claims process, which most large insurers and reinsurers don't have the capacity to handle, as it can be costly and time-consuming.

For example, Marsh has helped set up a clean hydrogen insurance facility, where developers pay an insurance premium, and Marsh negotiates insurance coverage with insurers to transfer the risk from the project owners' balance sheets. Investors (in this case, the insurers) provide capital investment for the projects, with their risk exposure mitigated by tailored insurance coverage. In the event of insured incidents, Marsh manages the claims process. The single platform helps lower costs for all involved.

It's hard to imagine a world where AI disrupts this process. It will certainly help streamline the paperwork, but the human touch of the Marsh brokers will always be required to navigate deals among key stakeholders. This business is highly profitable and cash-generative. The insurance arm booked an adjusted operating margin of 32% last year, compared with 21.1% for consulting. Of the $7.3 billion in adjusted operating income, $5.3 billion fell to the bottom line as operating cash flow. The company's return on invested capital, a measure of profit for every £1 invested in the business, is 25%.

How Marsh is embracing AI

The real AI threat is to Marsh's consulting arm, but even here, the company claims it is addressing the potential risk. In the company's first-quarter results, it said Oliver Wyman's AI Quotient, which helps firms deploy and scale AI tools, has advised on upwards of $50 billionin AI investment. This helped the consulting arm outperform in the first quarter, with Oliver Wyman recording revenue growth of 6%, ahead of group top-line growth of 4%.

Management is deploying these tools internally to help reduce costs. It's targeting a total of $400 million in savings over three years and has logged a 20% improvement in efficiency through AI-powered document processing. Other tools have saved an estimated one million hours of the team's time in the first year. UBS estimates this could help drive Marsh's return on invested capital to near 30% by the end of the decade.

So while the market frets about the risk AI poses, the company is quietly leveraging the technology to enhance its own services. This suggests that, if anything, the firm is an AI play.

Marsh's most important assets are its people and technology, and while it spends heavily on both, overall capital spending requirements are low. As a result, most of the cash generated from operations converts to free cash flow. Management has set out to return as much cash as possible to investors. At the end of last year, management authorised a $6 billion share buyback, with $750 million deployed in the first three months of the year. While the market was selling, Marsh was buying its own shares.

Cash flow is the firm's most attractive quality. While the shares might not look too cheap on a price-earnings basis, according to UBS, the shares are trading at a forward free cash-flow yield of 6.2% for 2026, 6.7% for 2027 and 8.1% for 2030.

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At Janus Henderson's North American Income Trust (NAIT) we focus on US income stocks – quality franchises that consistently generate cash and have disciplined capital-allocation policies focused on investment in the business to sustain competitive advantage while paying a progressive, covered dividend. Surplus cash beyond this may be used for bolt-on mergers and acquisitions, or to repurchase shares when the stock is dislocated from long-term assessments of fair value. The NAIT has a strong record of paying a progressive dividend and growing revenue reserves since the fund's inception in 2012 (it was converted from the Edinburgh Tracker Trust). The average dividend in the portfolio is 3% and dividend growth averages an attractive 6%-7%.

Our revenue reserves can comfortably cover one year of payouts and may be used if needed. However, there was only one small dividend cut during the 2020 pandemic period and none since then. Many UK investors may not automatically think of US income stocks, but there are several that offer attractive and growing dividends. The US has a history of superior earnings growth, which can often translate into higher dividend growth, too.

How to gain exposure to US income stocks

Dell (NYSE: DELL) is a technology infrastructure company uniquely positioned to grab a slice of the next wave of corporate spending on AI applications. Its scale, global supply chain and deep relationships with customers from the private and public sectors make it a preferred supplier of AI servers and data-storage technology. As enterprises move from experimentation to deployment, Dell will benefit from recurring technology update cycles. Growing profitability is supported by the company's shift toward higher-value technology infrastructure and its disciplined cost management. Debt has been cut and capital returns support the yield. We believe Dell's valuation fails fully to reflect the durability of demand and the firm's exposure to capital expenditure on AI.

Johnson & Johnson (NYSE: JNJ) is another US income stock that offers a rare combination of earnings quality and durable growth. Following the spin-off of its consumer-health division in 2023, it is a focused, innovation-driven pharmaceutical company and a leader in medical technology that should comfortably deliver mid-single-digit revenue growth. It has a diversified drug pipeline, which reduces risk, and its franchises in oncology, immunology and cardiovascular treatments are best-in-class, which will support cash flows in the long term. The medical-technology sector is growing strongly and the worst seems to be behind the company when it comes to legal issues. This is restoring investors' confidence and valuations. With a strong balance sheet, consistent free cash flow and a long record of dividend growth, Johnson & Johnson remains a core holding in volatile markets.

Morgan Stanley (NYSE: MS) is a global leader in the capital markets. Its earnings have become more resilient following a strategic pivot toward wealth and investment management, which generates stable, fee-based revenues. These annuity-like income streams provide downside protection while preserving upside exposure to appreciation in the markets and net asset inflows. The firm's strong capital position is enabling it to buy back shares and grow dividends. We believe Morgan Stanley's improved position will deliver impressive gains tied to long-term growth in the financial markets.

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“It's a market of stocks, not a stock market” is an old cliché, intended to remind us why investing is ultimately about how well individual companies are doing from the bottom up and not a top-down view of the FTSE 100 or S&P 500.

I don't entirely agree with this thinking, at least in the modern world. The growth of index investing has meant that many people now invest in the whole market or in broad sectors and don't care about the companies they hold. Money flowing in and out of funds can do more to determine whether valuations rise or fall than real changes in a business's fundamentals.

Still, it is always important not to let big-picture fears blind us to how well individual stocks are doing. If most companies are seeing robust earnings growth from the bottom up, it is likely that the overall index will keep going up. And right now, the reality is that earnings growth remains very strong in the US.

The year-over-year blended growth rate (ie, including both results reported so far and latest estimates) for the S&P 500 is currently 15.1%, according to FactSet – the sixth successive double-digit quarter. The index is expensive: at just over 7,100, it's on a trailing price/earnings ratio of 28. Yet if earnings keep compounding like that, it's not really a stretch to stay bullish.

The greatest threat to earnings growth

In the medium term (maybe three to five years), one has to wonder whether giant companies can continue to earn such high margins: the S&P 500 net margin is once again setting a new record of 13.4%. The geopolitical and political trends that let businesses – especially multinationals – become ever more profitable over several decades are shifting. Maybe this goes into reverse. But a few years is a lifetime in the markets and we are obviously not there yet.

In the shorter term (maybe a year or two), the extent to which AI mania is underpinning this boom cannot be ignored. In the tech sector, earnings growth is at 46%. There is a very fine line to be walked here: if all this investment does not bring huge productivity gains, it will grind to a halt. If it puts too many people out of stable employment, the political backlash could be equally dangerous. Yet all investors care about is what will happen in the next couple of quarters, and there is no sign of the boom letting up so far.

So what is the greatest ultra-short-term threat? Energy. The amount of oil at sea when the Middle East crisis started means that the consequences of the closure of the Strait of Hormuz and the shutting in of millions of barrels a day of crude is not really translating into shortages yet. Even if supplies resume tomorrow, there will be a lag and the effects will still show up over the next couple of months. But if they do not resume soon, the crunch is going to become very evident. A market focused on historic earnings and understandably upbeat forecasts is not pricing that in.

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“Nothing is as complex as cancer, which is aptly called the emperor of all maladies,” says Servaas Michielssens, head of healthcare at asset manager Candriam. The emperor has been expanding his dominion. The number of cancer cases has been on the rise recently. That's partly due to populations ageing, but is also a result of the fact that they're getting fatter. Worryingly, the average age of onset of some conditions, such as colorectal cancer, is getting younger and younger as a result, says healthcare investor Paul Major.

The earlier you catch the cancer, the better chance of survival and the less money that healthcare systems have to spend treating patients, says Moritz Dullinger of Pictet Asset Management. There is “a tremendous amount of excitement” among researchers about work to find new ways to detect cancer early. Cancer diagnostics is expected to improve in the years ahead, as Joseph Cordi, co-manager of the Impax Asset Management US Large Cap Strategy fund, points out.

Cancer diagnostics – “liquid biopsies” showing big promise

Most systems, especially in the US, are “set up for sickcare, not healthcare”, says Maryann Selfe, a global wealth and investment strategist and author of The Billion Dollar Blindspot: Why Women's Health Is the Investment Opportunity of Our Time. Diagnosis is therefore largely “reactive”, with the responsibility placed on patients to go and see their doctors when they have symptoms. But for many cancers, that may be too late – by the time symptoms have emerged, the cancer may have become untreatable.

Even the few proactive cancer screening programmes that currently exist have their limitations. Mammography, for example, has been proven to help spot breast cancer early, but it “doesn't necessarily spot all types of breast cancer equally well”, says Simon Vincent, chief scientific officer at Breast Cancer Now. That's especially true of lobular breast cancer, which accounts for around 15% of all breast cancers. Not everybody takes up the offer of going for mammograms – all the four parts of the UK are not currently meeting their targets – and the offer is limited to specific age ranges. Overworked GPs may be reluctant to order tests for those outside these groups.

Amanda Rice, founder and CEO of Chick Mission, who has survived cancer three times, has experienced such failings first hand. She went to the GP in her 30s concerned about her symptoms, but was dismissed by her doctor, who thought that at her age it was unlikely to be anything serious. She had to do a lot of pushing to get the tests she needed before she was formally diagnosed with breast cancer. Had she not been so persistent, she would probably have accepted her doctor's reassurance or skipped the additional tests because they were “so painful, invasive and costly”.

The limitations of traditional cancer diagnostic methods have led to a search for blood tests that can diagnose cancer. These “liquid biopsies” test for “circulating tumour DNA” (ctDNA), which are small fragments of DNA released into the bloodstream by cancer cells. The aim is to come up with tests sensitive enough to pick up even tiny amounts of such DNA and hence catch the disease at an early stage, says Major. Some tests screen for mutations associated with individual cancers, but the ultimate goal is to produce a “multi-cancer early detection test” (MCED) that can identify a range of cancers and which you can take every few years.

A big challenge is that any test needs not only to be sensitive enough to detect the presence of disease at an early stage, but also have the specificity to avoid large numbers of false-positives, which would clog up healthcare systems and cause patients unnecessary stress. It must also be affordable. Meeting all three criteria is tough. Diagnostic firm Grail's Galleri MCED recently failed in a large trial, which found that its test “wasn't quite effective enough and produced too many false-positives for the NHS to use”, says Major.

Despite these setbacks, there is optimism that liquid biopsies will become “incredibly valuable”, especially for cancers where there is no specific screening programme, or for ones that currently go undetected until they've started to spread around the body, says Vincent. The market for liquid biopsies was already worth between $5 billion and $10 billion in 2025 and is estimated to reach $10 billion-$20 billion by the end of the decade, reckons Erin Xie, managing director and portfolio manager for health sciences at BlackRock.

Blood tests that screen for a wider range of potential signs of cancer are likely to be more successful in diagnosing cancer than those which use ctDNA alone, says Major. One company working on this is DXcover, which was spun out of the University of Strathclyde, Glasgow. Its MCED screens for proteins, lipids and carbohydrates as well as DNA to detect whether cancer is present, its CEO Matthew Baker explains. Trials have suggested that such tests can detect malignant brain cancer with a sensitivity of 86%, even though only a small number of brain cancers shed ctDNA. They might also detect a broader range of cancers at the very earliest stages.

Some cancer diagnostic tests might not even need a blood sample. A test developed by Serox, for example, uses surface-enhanced raman spectroscopy to identify cancer in urine in under three minutes. That makes it much easier to screen, as getting samples will not require trained phlebotomists, as Serox's founder and CEO Cici Muldoon explains. Serox is working on a lateral-flow style stick that works in a similar way to a pregnancy test. Serox is still in the early stages of raising money and is working with John Radcliffe Hospital in the UK and Massachusetts General Hospital in the US.

From diagnosis to treatment

Detecting disease is “only part of the equation”, says Michielssens. Cancer diagnostic tests also have a role to play in directing treatment (companion diagnostics) and in detecting minimal residual disease (MRD) – the small number of cancer cells that may remain in the body following otherwise successful treatment. They can also help determine whether a treatment is working. For example, ctDNA is released when tumour cells die, so a sudden increase in levels of ctDNA immediately after treatment can indicate that the treatment is working.

Similarly, other more complex genetic tests, including those provided by companies such as PacBio, “can give an indication as to whether a patient's cancer is becoming resistant to a particular treatment”, says vice-president Neil Ward.

Another company operating in the area where cancer diagnostics and personalised medicine overlap is CanCertain, which has developed a test that enables clinicians to “pre-screen cancer treatments on the patient's own cells”, says its business development director Dharmesh Mehta. Circulating tumour cells are extracted from patients' blood and then exposed to potential treatments so that the oncologist knows in advance what is likely to work and what is likely to fail. CanCertain is working with The Christie NHS Foundation Trust in Manchester and the University of Leeds to test the technology.

Even if initial therapies treat the cancer successfully, patients typically have to undergo adjuvant treatments, such as chemotherapy and radiotherapy, to eliminate any lingering cancer cells. Patients are then monitored to see if there is any evidence that the cancer has come back, says Gareth Powell, head of healthcare at Polar Capital. Liquid biopsies may in many cases reduce the need for adjuvant therapy and enable quicker follow-up treatment if the cancer returns, says Powell. The fact that there are nearly 20 million cancer survivors in the US alone suggests that there is a great demand for accurate MRD tests, says Michielssens.

A revolution in scanning technology

Alongside the development of more efficient blood tests, imaging and radiology is also starting to undergo its own revolution. While the average MRI machine “isn't fundamentally different from the first machines produced by Peter Mansfield and his team nearly 50 years ago, they are lighter, can fit in smaller locations and don't need as much power”, says Lizzie Tuckey, managing director at imaging platform Scan.com. Advances in AI are also transforming the software that is used in the machines.

AI has made the process of taking a large number of images of the body and then combining them much more efficient, allowing radiologists to get away with fewer images without reducing the quality of the final image. This in turns means that each patient now needs to spend less time inside the scanner, which means that more patients can be scanned, bringing down costs. In the case of CT scans, the fact that the patient is in the scanner for less time means that their exposure to radiation is reduced. AI is also very good at spotting small changes over time.

One firm using AI to cut both the cost and duration of MRI scans is Ezra, part of Function Health. Ezra already offers comprehensive scans for most organs and tissues, which take only 22 minutes, “typically the time most other providers would take to scan a single major organ”, says founder and CEO Emi Gal. The firm hopes that by next year it will have reduced this time to 15 minutes and has set a medium-term target of five minutes for repeat visits.

Such a premium product comes at a price – Ezra's multi-organ scan currently costs £1,299 in the UK. But prices are falling and Gal indicates that he hopes to cut the US price to around $500 soon. Once this happens, having an annual MRI scan to track all sorts of changes in the body “could become something that everyone does, in the same way that we give smokers low-dose CT to screen for lung cancer, or give women who are over a specific age regular mammograms”.

Going forward, the technology is only likely to continue to make scans quicker and cheaper as we already see in the “explosion” in the number of patents filed (traditionally a good leading indicator of future development) and the number of devices approved. At the time of writing, the Food and Drug administration, the US regulator, has approved 1,451 AI-enabled medical devices, “of which around 80% are in the field of radiology”, say Robert Wiseman, Rob Sackin and Alexander Frank of Reddie & Grose patent and trade mark attorneys.

Improving the patient's journey

As well as improving medical imaging, Wiseman, Sacklin and Frank think that AI could help speed up blockages in “the patient's journey”, by making sure that patients get referred to the right specialists, that the proper tests are carried out, and that these tests are then analysed appropriately. The legal uncertainty surrounding software patents makes this sort of development less publicly visible, but they reckon that beneath the surface there is plenty of work going on in this area.

One company at the forefront of using AI to bring together the vast amount of medical information available to doctors is xCures, a service platform that “basically aggregates, organises and structures medical records”, says CEO Mika Newton. Instead of doctors “having to read thousands of pages of medical records and then manually input the information into their own system, the information can automatically be extracted, enabling them to see all the important information quickly”. The technology can, for example, convert unstructured records, such as scans and medical notes, into a more structured form.

In the longer run, speeding up the flow of information through the medical system could be helpful in cancer diagnostics, enabling researchers to find new connections between various symptoms and cancers that human researchers might be unable to spot on their own.

Only 5% of cancer patients are currently involved in some sort of clinical trial, so opening up medical records in this way (with appropriate consent) could speed up developments in both the diagnosis and treatment of cancer.

AI can also help hospitals and healthcare systems decide how to choose between the various cancer tests that are suddenly appearing on the market – many of which are built by small companies with very specific applications, say Flann Horgan and Mitchell Goldberg of NTT Data. NTT Data has recently developed a platform, in conjunction with the Royal Marsden Hospital and the Institute of Cancer Research, that helps researchers “evaluate lots of different algorithms without having to fly all over the world, and then integrate them into their workflow”.

The best cancer diagnostic investments to buy now

Until recently, one of the leading players in the liquid biopsy market was Exact Sciences. It had several of its tests approved and had developed Cancerguard, a separate blood-based multi-cancer early detection (MCED) test. This year, the firm was acquired by Abbott Laboratories (NYSE: ABT). While liquid biopsy is only part of Abbott, which also sells medicines and cardiovascular devices, the deal gives Abbott a strong foothold in the area. Indeed, Grégoire Biollaz of Pictet Asset Management points out that Exact Sciences with its high-teens revenue growth adds a faster-growing segment to Abbot's Diagnostics division. Abbott trades at 17 times expected 2027 earnings and pays a yield of 2.5%.

A purer play on liquid biopsies is Guardant Health (Nasdaq: GH). It has already had a blood test for colorectal cancer approved – a more convenient alternative to the current stool-based test. The colorectal test is, however, really “just a proof of concept” for Guardant's more ambitious medium-term plans for further MCED tests, says healthcare investor Paul Major. Guardant is also developing tests that will help guide treatment as well as one to detect residual levels of cancer. It isn't yet making any profit, but its revenues more than tripled between 2020 and 2025.

Major is also a big fan of Adaptive Biotechnologies (Nasdaq: ADPT). It has already developed clonoseq, a test approved by the US regulator to detect the presence of residual tumour cells in lymphoid cancers. It can be used to inform decisions around treatment, sparing many patients unnecessary chemotherapy, and is also used by many drug companies in clinical trials to evaluate the effectiveness of drugs. Like many biotechnology companies, it is currently losing money, but sales are rocketing. Major believes that it is a prime takeover target for a large company looking to acquire its core technology.

The leading imaging company in the US is RadNet (Nasdaq: RDNT). As Polar Capital's Gareth Powell explains, RadNet has found a way to undercut hospitals, which means that many US insurance companies will try to get patients to use the company's services. It has been investing large sums in developing AI that can read scans, which has been validated in clinical studies, and the firm is in the process of rolling it out. The stock trades at a pricey 57 times estimated 2027 earnings, but revenues have essentially doubled between 2020 and 2025. It is expected to keep on growing strongly.

Siemens Healthineers (Frankfurt: SHL) is “in a very good position” when it comes to producing MRI and CT scanners, say Dullinger and Biollaz. Siemens also makes a wide range of medical devices and its laboratory division will benefit from any rise in the volume of blood tests being carried out. Sales have grown by two-thirds between 2020 and 2025 and the stock trades at only 15 times 2027 earnings. The yield is 2.9%.

Finally, Dan Buckley of Daytrading.com likes Illumina (Nasdaq: ILMN). It provides a lot of the infrastructure necessary in the use of genomics in diagnosing cancer and the use of diagnostics in informing treatment. The stock trades at 23 times 2027 earnings.

This article was first published in MoneyWeek's magazine. Enjoy exclusive early access to news, opinion and analysis from our team of financial experts with a MoneyWeek subscription.

YouGov (LSE: YOU), the market research and data-as-a-service (DaaS) business, was founded by Stephan Shakespeare and Nadhim Zahawi just after the late-1990s internet bubble had burst. Its original aim was to bring political polling into the internet age.

Traditionally, market research and political polling relied on methods such as telephone polls and face-to-face street interviews. Notoriously, voters are reluctant to admit to voting Tory when questioned, because they feel embarrassed. Answering questions online would reveal their true preferences, it was thought.

Existing pollsters argued that YouGov's samples were skewed as they would naturally favour tech-savvy younger people, but YouGov made the best predictions for both the 2001 and 2005 general elections.

For Shakespeare and Zahawi, the political polling was a loss leader for their far more lucrative business offering research into corporate brands. YouGov's polls were often quoted in the media, which raised awareness and was effectively free advertising.

YouGov listed on the Aim junior market through a placing at 135p (implying a market capitalisation of £18 million) in 2005. The management then used the capital raised to launch BrandIndex, a daily, brand-tracking platform that was always on. BrandIndex now tracks consumers' perceptions of more than 27,000 brands across 56 markets worldwide, powered by a panel of more than 30 million registered members. Respondents are paid in points or cash for filling in the surveys.

The key insight was that the platform could collect valuable data and sell subscriptions to many clients: brands, marketing groups, agencies, management consultancies, even hedge funds looking for an edge on how consumers were switching loyalties. This proved phenomenally successful. In the decade to 2023, revenue quadrupled, while profits grew from less than £1 million to £45 million. The share price rose in value 25 times, creating tens of millions of capital gains for the co-founders.

Is YouGov under threat?

Problems started to emerge a couple of years ago, when marketers began to question the quality of the data. YouGov admitted that the rise of “survey farms”, where people in low-income countries were paid to click through surveys, fraudulently picking a random answer, has been a major challenge. More recently, these human survey farms have been replaced by “AI bot farms”, where the fraud has been automated. This has created a major headache for YouGov, as paying customers lost confidence in market research.

In response, YouGov focused on more rigorous identification and verification, but that has made the process of signing up to a panel more onerous, running the risk of discouraging people who don't want the hassle, leaving a higher percentage of bots in the pool. On the most recent results call, management talked about investing to improve the experience of panellists. Relatedly, some of YouGov's customers could be tempted to bypass BrandIndex and instead use AI to create data that is almost free and instantly available. A CEO planning a major acquisition is unlikely to rely on such synthetic data, but if AI produces results that are “good enough” most of the time, the threat to YouGov is clear.

A second problem emerged after management bought German research firm GfK's Consumer Panel Services business for €315 million in July 2023. Rather than asking what people think, the newly acquired business (now called Shopper) focuses on what people actually buy. Shopper's customers, the corporations that buy the data, tend to be in the fast-moving consumer goods (FMCG) and retail sectors, who are reluctant to spend on market research when interest rates rise and household finances come under pressure. Shopper has high fixed costs, paying tens of thousands of households rewards for recording their shopping behaviour. When the division's sales missed targets, those fixed costs meant a profit warning followed.

So the GfK business looks to have been dearly bought. YouGov paid around ten times EV/Ebitda, a key measure of value in acquisition deals. That's two and a half times YouGov's current EV/Ebitda of four times. Of the proceeds, £50 million were funded with a placing at £9.20 per share – the current price is £1.73. Management has acknowledged the poor performance, launching a strategic review that will look at both a possible disposal of Shopper or deeper integration into the core group. In the meantime, YouGov has committed to putting £6 million into Shopper as investment is required to sustain growth. That may well be the correct strategic choice, but it will result in a hit to margins at a time when the division's revenues have fallen 2% on an underlying basis.

So investors are seeing downward pressure on group earnings per share (EPS). Management has expressed confidence that the payback will be rapid and margins will rebound, with the first wave of its “value delivery plan” producing a forecast £2.5 million of profitability by the 2027 fiscal year. Later, the company will seek to exploit AI to drive a “step change” in margins. Over the last decade, operating margins averaged 12.5%, compared with 8% in 2025, according to ShareScope. Thus, even a return to the ten-year average would be a positive and a significant improvement, and drive a fundamental re-rating. That said, management teams always exude confidence during the investment phase of a turnaround situation. Management has said it expects improving margins, but has been more cautious about saying what it expects future revenue growth to be.

YouGov does seem to own unique assets, selling access to a massive “living” database of consumers' opinions. AI has the potential to automate and reduce the cost of gathering this data. But the potential of AI to improve performance is yet to show up in the numbers. Last month, the company reported underlying revenue up just 2% to £195 million and adjusted profits before tax were down 30% to £17 million. The board has decided to scrap the dividend once the company has refinanced its £160 million net debt and aims to launch a buyback instead. That's certainly a bold decision with net debt at 2.1 times Ebitda and EPS forecasts declining.

YouGov's problems pre-date the rise of AI, though. There was a nasty profit warning when the shares fell 40% in June 2024, when the company warned that revenue growth was below expectations. Management blamed increased price competition and pressure on clients' budgets. Unfortunately, that warning came three months after management had reassured investors that the sales pipeline was healthy, with more than 75% of revenue committed.

Co-founder Stephan Shakespeare stepped back into the CEO role in early 2025 to turn things around. Yet the share price has continued to decline and the board has begun looking for a new boss. Shakespeare is expected to remain in the role until the firm is “well positioned for its next stage of growth”. He currently owns less than 2% of the group, and his planned departure even as the turnaround fails to gain momentum is unlikely to be seen as a vote of confidence. Moreover, his personal stake is down from 8% in November 2020, as he sold most of his shares at a price between 900p and 1,150p – receiving more than £50 million in value before the stock's significant decline in 2024. More recently, he has been buying, in August and October 2025, but only 126,000 shares, worth significantly less than half a million pounds. Currently, the shares are trading on a price-earnings (p/e) ratio of five times forecast earnings, indicating scepticism about the turnaround plan. The shares are also trading below their 50-day moving average.

How YouGov made a classic mistake

YouGov looks like a classic case of a successful business running into problems after using debt to fund a poor acquisition. Investors reacted badly to the move to scrap the £10 million dividend and replace it with a share buyback, with the shares down another 10% following the first-half results, which came out at the end of March. If management can turn things around, then investors will be richly rewarded – but if performance continues to struggle, then that buyback increases balance-sheet risk. Management describes YouGov's balance sheet as “solid”, but the reality is that £418 million, or three-quarters of total assets, are represented by goodwill and intangible assets. Deducting that sum from shareholders' equity reveals that tangible net assets are a negative £232 million. As a data business, YouGov wouldn't be expected to have a balance sheet full of property, plant or equipment, but the lack of backing from tangible assets wouldn't matter if revenues were growing strongly and the most recent acquisition was deemed a success. That's not currently the case.

The shares peaked at £16 at the end of 2021 and the share count has only increased 5% since then. The risk/reward ratio is well understood by the market and I don't own the shares, but I am keeping a close eye on the stock. In these situations, I prefer not to try to call the share-price bottom, but to wait for evidence that the firm can return to its record of revenue growth. An investor might miss out on the first 10%-20% of the bounce, but is also less likely to “catch a falling knife”.

This article was first published in MoneyWeek's magazine. Enjoy exclusive early access to news, opinion and analysis from our team of financial experts with a MoneyWeek subscription.

For many years, software-as-a-service (SaaS) firms, which provide the digital utilities we use every day, such as Microsoft 365, have been prized for their consistent high returns. They are known for their high margins and predictable revenue and have become the foundation of many high-quality investment portfolios. People saw them as “fortress” businesses that could survive any economic conditions. However, in the first few months of 2026, that reputation has been shattered. A massive wave of selling has hit the sector, leaving many of the world's most highly regarded firms trading at their lowest valuations in years.

This drop comes from a growing fear about the AI revolution. Many now worry that AI might replace some of these companies entirely. The sell-off has been referred to as the “SaaSpocalypse”. It has created a major divide in the market. One side believes the SaaS industry is in permanent decline. The other sees a rare chance to buy superb businesses at a discount. The challenge is to tell the difference between a real risk and a distraction. That requires an understanding of where a company actually gets its strength and whether a piece of software is just a tool that anyone can copy.

Software-as-a-service firms fear AI could dismantle their business model

We are moving from a world where software was just a tool to one where software acts as an autonomous agent. This is easily the biggest change in the way business is done since the internet first arrived and might yet rival the industrial revolution in terms of impact. The fear for software firms is that AI might soon dismantle their competitive position. Things came to a head when one of the world's largest AI companies, Anthropic, released its latest tools, Cowork.

Part of the strength of software-as-a-service businesses is perceived to be the difficulty of writing and deploying code. Cowork threatened this by offering natural language programming. Essentially, anyone who can speak clear English can now code software into existence without having to learn how to code. For a few years now, AI has been a useful tool in helping coders improve their code, but Cowork goes beyond this. It can build a customised tool to manage specific work in comparatively little time. The reaction was panic.

The argument goes that if a non-coder can speak a project-management tool into existence, then why would they pay for an expensive software system designed by a third party? This threat of zero-barrier entry is what caused the SaaSpocalypse. Investors looked at the huge profit margins of SaaS businesses and instead of seeing it as a strength, as they have for years, they saw a target. There is a fear that white-collar work, such as processing invoices, will become commoditised. If the work of a lawyer or an accountant is mostly about following a process, then the software helping them is suddenly very vulnerable to a cheaper and faster AI alternative.

However, this fear might overlook how businesses actually work. The biggest threat from Cowork might not be to the software owners, but to the people using it. We are seeing a huge disruption in jobs because AI is great at replacing process-heavy tasks, such as auditing or conveyancing. Perhaps the most extreme example was fintech company Block, which recently announced that it would cut its staff from 10,000 to fewer than 6,000, with CEO Jack Dorsey saying, “intelligence tools have changed what it means to build and run a company”. Most probably, there will be many more similar announcements in the coming months and years.

But while the threat to jobs is clear, better or cheaper software doesn't always replace an established one. This is where the market seems to misunderstand the advantage of being the established player in a market. The strength of a business such as Sage, for example, which provides accountancy software to thousands of small businesses in the UK, isn't just about its range of features. Rather the software serves as a system of record; the single, trusted source of truth for the most sensitive data a business has.

Understanding nuance will bring profits

For the typical Sage user, the software is a tiny part of their costs, but their entire internal process is built around it. Switching to a cheaper AI-built alternative involves far more than “vibe coding” a replacement. Vibe coding is where a user describes the “vibe” or desired outcome of a program in plain English, and the AI writes the code, but relying on this for critical infrastructure involves a massive risk to the business. If an AI-generated tool makes a mistake, the consequences can be catastrophic. Even before the advent of AI coding tools such as Cowork, software testing has been a longer and more important process than the creation of the software itself.

There is also the so-called maintenance trap. Once software is being used it needs to be improved over time to meet the changing needs of customers. Building a prototype with Cowork is almost free, but maintaining that code and keeping it secure is a different problem altogether. Most businesses would rather outsource that responsibility to another company that stays on top of relevant law than carry the risk of mistakes themselves. For many, a third-party guarantee is worth more than the savings from using AI instead.

One area where software-as-a-service businesses might suffer is where they charge on a per-user or per-licence basis. Using Block's sharp reduction in staff as an example, if AI makes a worker twice as productive, a company might decide it needs 50% fewer workers. That means 50% fewer software licences to pay for. This is a problem for SaaS businesses that make money based on the number of people using their platform. To counter this, we will probably see a shift away from per-licence pricing toward models based on outcomes or usage. The winners will be the ones who can move from being a tool for individuals to becoming an enterprise-level system. The recent sell-off shows that the market hasn't distinguished between simple per-licence software and the mission-critical infrastructure that is built into the rules of a business.

The disruption is real, but it has layers. A new AI start-up can build a better sales tracker, but it can't easily build years of trust or a global network of trained users. In professional services, the skill that AI replaces is often just the manual part of the work. The value the software provider offers is the governance, the audit trail and the legal protection. As “vibe coding” becomes a more viable way to develop software, it allows more people to build their own tools. These unmanaged tools could, if not implemented with care, create a mess of data silos. That chaos often leads businesses back to the safety of a professional suite where the data are clean and there is a human to call when things go wrong.

The job of an investor is to find where the protection remains intact despite these technical challenges. AI is definitely pushing down the cost of making software, which theoretically could hurt profitability. However, it is also pushing down the internal costs for big software companies. A business such as Constellation Software, for example, can now maintain its products with much more efficiency. This could lead to rising profit margins even if growth slows down. The market panic has been so bad that it has treated every company the same. This lack of nuance creates opportunity for investors. If you look past the headlines about the death of software, there remain enduring moats built around mission-critical parts of a business or the long-term systems of record. Making sense of this really comes down to the difference between a simple software tool and the essential infrastructure a business cannot live without. When a firm handles the vital but repetitive tasks for an organisation, it becomes the main protector of its data and its processes.

The businesses well placed to survive the 'SaaSpocalypse'

The real opportunities are found in the businesses that control the primary system of record. These are much more valuable than the companies that just provide a tool for people to do their work. Sage Group (LSE: SGE), for example, is a perfect example of a business protected by its place in a company's daily workflow. It provides the accounting and payroll software that small businesses across the UK rely on. Many firms are required by law to use these tools for tax compliance. For most of them, the cost of Sage is a tiny part of their overall bills, but the risk of switching to another provider is massive. Staff are already trained on the system and moving years of data is a technical nightmare. In early 2026, Sage reported that its new AI tools were saving customers between five and ten hours of work every week on administrative tasks. This makes the product even more vital and should keep the steady subscription income flowing.

Experian (LSE: EXPN) is the world's largest credit bureau and manages 1.3 billion data updates every month. In a digital world that is currently struggling with fake identities made by AI, Experian's verified credit histories have become a vital filter for the global banking system. Its tools for analysis and decision-making are built into the lending platforms of major banks. The firm saw its organic revenue growth accelerate to 8% in late 2025. As banks need accuracy when they make lending decisions, they are unlikely to swap a trusted data source for unverified AI models. It has a vast dataset that third-party AI models are unable to train on and this control over data allows Experian to protect the business while its internal AI models can improve the quality of the analytics it provides.

Constellation Software (Toronto: CSU) is the owner of hundreds of tiny, niche software companies that handle essential tasks, such as bus routes or hospital billing. The cost of the software to the customer is usually low, but its importance is huge. The chance of a new AI start-up copying thousands of these specialised workflows is slim. And by using tools such as Cowork, Constellation is in a good place, cost-effectively to improve the software it sells. Moreover, the firm is currently using its cash to buy up tiny software businesses that have seen their prices fall due to fears about AI. By applying its own efficiency rules to these new buys, Constellation is turning the market's panic into growth.

Oracle (NYSE: ORCL) has moved past its old image of just being a database firm and is now a vital part of the AI sector. It makes up the digital plumbing of the global economy, handling everything from airline bookings to national banking systems. It has a huge advantage because it holds the key private data that AI needs to function. It is also putting serious money into the physical side of the business, with billions going into high-end data centres. This spending is massive and it has caused some tension in the market, but moving these essential tasks to a different provider is so difficult that customers tend to stay put.

Intuit (Nasdaq: INTU) is a similar business to Sage, but with different geographic exposures. It has successfully integrated AI into its business with its tax-agent model reportedly helping to find extra deductions that business customers were previously missing. These kinds of savings can quickly repay the modest cost of its QuickBooks service and has led to a customer retention rate of around 85%. For small businesses, QuickBooks Online serves as the main ledger and payroll system. While the tech for simple accounting has become cheaper, the difficulty of moving old financial data creates a very lasting relationship. Intuit is using AI to move into live services, further embedding it in customers' workflows. This helps protect the firm against any loss of income from having fewer people use the software. As with Sage, Intuit's software remains a necessity for smaller and mid-sized companies.

Relx (LSE: RELX) has moved on from being an old-fashioned publisher of journals such as The Lancet to becoming a provider of data analytics. By 2026, revenue from paper journals dropped to just 4% of its total sales as the business moved almost entirely online. Its legal and medical data sits behind private paywalls and is verified by experts. This archive is arguably where the value lies even should AI agents be used to analyse the data. However, there is a threat from general AI models that might become good enough for basic legal research. Relx needs to make sure its high-end tools are distinguishable from cheaper, more basic AI options.

Wolters Kluwer (Amsterdam: WKL) is similar to Relx and works in areas where large portions of digital revenue come from AI-powered tools. Its model uses experts to check the work to ensure that its medical and tax insights can be defended in court. The company's UpToDate platform is linked to improved patient outcomes in hospitals, which partly justifies its high prices. Even so, the firm has to spend a lot of money to stay ahead and it is investing heavily in product development to beat off new AI challengers. Profit margins are expected to hit 28% in 2026, but the long-term cost of staying ahead is something investors will have to watch.

SAP (Frankfurt: SAP) is in the middle of a massive project to move its vast global customer base over to the cloud. This is a slow and complicated process, but the numbers show that it is starting to pay off. The company's main push is a program called RISE with SAP. It is in an advantageous position because its systems serve as the operational backbone for major organisations. However, this is a double-edged sword as its customers are also in a better position to develop and implement cheaper customised systems.

Salesforce (NYSE: CRM) is a leader in its field, but is facing a problem in that its customers need fewer white-collar workers. The company's Agentforce product has grown very fast from a small base. But if AI agents allow one person to do the work of several, firms will need to pay for fewer licences from companies such as Salesforce. Its traditional way of making money from fees paid per licence is vulnerable to AI.

Adobe (Nasdaq: ADBE), owner of Photoshop, faces a direct threat. AI content-generation could make traditional licences less valuable. Professional designers still rely on Adobe, but casual users can now use AI tools for basic design tasks and, in time, the value of creative work could diminish as AI tools improve and companies reduce budgets. This creates a problem where the company must use AI to remain relevant while possibly hurting its own subscription numbers. The challenge for Adobe is to prove that it is worth the cost when simpler AI alternatives are ubiquitous.

The best software-as-a-service buys for UK investors

For UK investors, Sage and Experian look like some of the safest bets. Sage is built directly into the regulatory rules that British small businesses have to follow. This makes its software an essential service rather than just a tool you can choose to replace on a whim. As the firm moves toward automated accounting, it is more likely to grow its margins than lose its customers. Similarly, Experian has a massive data barrier that AI cannot easily copy. In a world where AI-generated fraud is becoming a bigger problem, verified data is incredibly important. This creates a safety net for banks.

Outside of the UK, Oracle is a strong way to invest in AI infrastructure without paying the extreme prices found elsewhere in tech. By controlling the database layer and putting billions into physical data centres, it remains a major part of corporate infrastructure across the world. Intuit also seems well-placed to handle this shift. Its AI features are already saving real money for its customers. Finally, Constellation Software continues to be expert at buying mission-critical niche businesses. It is exploiting market fears to buy up small businesses at a discount. It is using the panic to fuel its own growth.

AI is undoubtedly going to change how we work. We are entering a time where tasks that rely on a set process are being automated at a fast pace. However, the recent sell-off in the software sector has been blind. It has ignored the fundamental difference between a simple tool and something that is vital to the business. If you can separate the businesses that own and offer mission-critical services from those that merely sell a tool, you can find top-tier companies at prices that don't reflect their long-term value.

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It is an audacious bid. Through his hedge fund Pershing Square, Bill Ackman has offered $64 billion for Universal Music, one of the largest music conglomerates in the world and a producer for artists including Taylor Swift.

It is a complex deal involving both cash and shares and would move the company's listing from Amsterdam to New York.

It remains to be seen whether the deal is successful or not. The decision will probably rest with French billionaire Vincent Bolloré, who controls 18% of the company, and on its British chief executive Lucian Grainge, who is widely credited with managing the transition from analogue to digital music. Predictions markets are giving the bid a 37% chance of success by 30 June.

It is far from the only recent media megadeal. After a battle with Netflix, Paramount Skydance, which is controlled and financed by the Ellison family, has agreed to pay more than $100 billion for Warner Bros, the studio that controls a huge library of films, along with news channel CNN and sports broadcaster TNT. It still needs regulatory approval in the markets where it operates, but the deal is agreed, and there is little to stop it from happening now.

Investors are betting against AI slop

There is a common theme to both major bids. Huge sums of money are being wagered on the proposition that the arts will still be created and controlled by humans. That goes against the hype in the rest of the market.

We have read huge amounts about the rise of AI and the vast sums being poured into the software and data centres that will power super-smart chatbots. The leading companies in the sector, such as OpenAI and Anthropic, may well be worth more than $1 trillion if they list their shares later this year, while established giants such as Google, Meta and Elon Musk's X have been pouring fortunes into developing their own systems.

The creative industries are meant to be right in the firing line to be replaced by AI. The bots are good at generating music tracks that can be surprisingly popular. There have been plenty of AI-generated songs that have topped the streaming charts, and the likes of ChatGPT and Google Gemini offer music-generating tools. It is not hard to choose a genre, come up with a theme, and then upload a track onto Spotify or Google Music. It can be very lucrative.

Likewise, AI actors can replace real ones, and the same is true of scriptwriters, technicians and directors. Indeed, Netflix last month paid $600 million for InterPositive, an AI start-up developing post-production tools for the film industry, backed by the actor Ben Affleck. There are already reports of AI helping with scripts, and it may not be long before the bots are up on the big screen.

So why would anyone in their right mind want to pay tens of billions for a film studio or a music label? After all, there is not much value in a studio if films can be created by anyone with a laptop and a subscription to ChatGPT or Claude AI.

Conventional wisdom says the world will soon be flooded with AI slop – films of every conceivable genre, written for you, directed in any style you choose, and acted by AI-generated bots, or else by digitally recreated megastars from the past. Every taste will be catered to, and it may not be long before you can choose from a range of plot twists or endings depending on your personal taste. Traditional films will be finished.

Likewise, the streaming apps will also soon be flooded with AI slop – Taylor Swift knockoffs, along with tracks from every possible musical style, from classical to jazz to soul. We will all be able to create our own personal track-lists, made up of a mash-up of styles, singers and musicians precisely tailored to our own tastes or mood.

AI slop cannot create anything new

Well, perhaps. Yet the billionaire bidders for Warner and Universal are clearly on to something. In the end, human creativity will survive. The chatbots can recreate plots or tunes that already exist, study the libraries and rustle up a reasonable facsimile. But they can't create anything new; they don't have personality, they don't have any insight into our feelings, and they are never going to be able to make us laugh, cry or dance.

The chatbots might change the way industries function, but they are unlikely to destroy them. Investors are pouring huge sums of money into AI start-ups, confident that the systems will be able to replace just about any form of human endeavour.

Some of the world's richest people are betting the other way – against the triumph of AI slop. So should ordinary investors.

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What is stopping the UK from investing? It's a mixture of three main factors, according to Henry MacLeod, co-head of digital distribution at BlackRock.

In this episode of MoneyWeek Talks, Kalpana Fitzpatrick speaks to Henry about the state of investing in the UK, how we can debunk myths about risk, and whether AI can help you become a better investor.

Watch the full episode on our YouTube channel or on any podcast platform.

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MoneyWeek Talks is a podcast that helps you unlock the secrets to financial success. Editors Kalpana Fitzpatrick and Andrew Van Sickle are joined by influential guests – from CEOs and entrepreneurs to economists and policymakers – to share their top tips on managing money, investing wisely and building wealth.

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Robotics “will soon be the largest market that we have ever seen”, says Mark Minevich, an AI strategist, and president and founding partner of Going Global Ventures.

One of the big limitations of artificial intelligence (AI) at the present time is that, in the words of an advertisement I spotted on the London Underground recently, ChatGPT can't mend a broken pipe.

Chatbots may not be able to physically fix things, but robotics is undergoing its own revolution, says Steve Brotman, the founder and managing partner of Alpha Partners. He predicts that “the use of robotics as the physical embodiment of AI will be a total gamechanger”.

By 2030, there will be a cumulative total of one million installed robots, predicts Junwei Hafner-Cai, a senior analyst in the Polar Capital Sustainable Thematic Equity team. By 2040 it'll be 100 million, and by 2050 one billion. Robots are “increasingly able to execute intricate tasks previously reserved for skilled human labour”, says Yan Taw Boon, a fund manager at Neuberger Berman. That paves the way for factories, logistics hubs and even service industries to be disrupted.

For robotics, AI is the biggest game-changer

The single biggest force driving advances in robotics is AI, says Anjali Bastianpillai, a senior client portfolio manager at Pictet Asset Management. “Physical AI” – by which is meant its integration with human-like robots and other machines – will be the third pillar of the AI revolution, says Bastianpillai, and will be as important as the huge amounts of money being used to build data centres and the efforts to use AI to power a new generation of intelligent software. Advances in “reinforcement learning” mean that robots can now improve through trial and error, allowing them to “adapt to new environments far more effectively than before”, says Darius McDermott, a managing director at FundCalibre.

These advances in AI are taking place alongside hardware improvements that enable robots to do things traditionally considered too complicated for them, such as walking, picking up a box on their own, or manipulating an item with their hands, says Minevich. We are quickly moving from a situation where robots were “fixed in place and programmed to do one simple task”, to autonomous machines that “adapt to their surroundings, make decisions on their own and are able to do more than one task”.

Rapid improvements in robot technology have been followed by a surge in interest from companies, which want to “protect margins and get a good return on investment”, while dealing with the pressures created by the collapse of global supply chains, says Minevich. Faced with the need to move production back to countries with “ageing populations and rising wages”, robotics is increasingly seen as a solution that can help companies maintain profits and productivity. This could also benefit society, as Richard Clode of The Bankers Investment Trust argues. If we don't “embrace” robotics, he says, “we will not have enough workers to produce the GDP growth and taxes to pay for an ageing population”.

Companies are already “much more willing to adopt robots than they used to be”, says Valentin Antoine of TDK Ventures. Some “holdouts” and sceptics remain, but the fact that early adopters are “seeing tangible returns on investment” is changing minds at the executive suite and boardroom level. Antoine likens the demand for robots today to that for computers a few years after the first affordable models started to hit the market. The levels of interest and rate of adoption is already much higher than it was even three years ago, he says.

Robots have already taken over factories

Factories have long employed robots in some form, of course, so it's little surprise that industry will be at the forefront of the revolution, not least because the economics are so compelling. Research suggests that, at wages of $20 per hour, it takes just six years for an investment in a humanoid manufacturing robot to pay off, says Hafner-Cai. Given the projected fall in the price of such robots, this payback period will fall to just 1.7 years by the end of the decade and to around three months by 2050, even if wages stay the same.

Many companies are already quietly piloting the use of humanoid industrial robots, says Brotman, and within five years companies that don't have them in their facilities will be at a competitive disadvantage. Some Chinese firms already use “dark factories”, so called because they don't need any lights, as there are no humans there. Chinese factories that aren't using robots themselves may well now be giving their factory workers lots of gadgets and cameras that will provide the training data for tomorrow's droids, says Sam Hields, a partner at venture-capital firm OpenOcean.

The idea of empty factories and human workers inadvertently training themselves out of a job may seem a little dystopian, but Hields emphasises that robots can also improve safety by taking over some of the most dangerous and dirty jobs. OpenOcean has recently invested in Sitegeist, for example, a start-up that has made a robot for hydro-demolition – using water at very high pressures to remove concrete. Human doing the work can only stand it for 20 minutes at a time. Robots can work for much longer, as well as map the progress of what is taking place.

Robots head out on the highway

Robots are also starting to play an increasing role in retail and logistics. These sectors are vital to our modern on-demand economy and create a lot of jobs “that can be very difficult for workers, due to the sheer tedium of checking and transporting thousands of items each day”, says David Pinn, CEO of real-world AI firm Brain Corp. The ability of robots to “understand the environment in which they are operating” means they can now start doing more work previously done by humans, including such tasks as scanning shelves to find products that are out of stock, or have missing price labels and products. Enthusiasm for stockroom and warehouse automation is spreading from cutting-edge retailers such as Walmart to other supermarkets and big stores. Robots powered by BrainCorp’s AI are now being deployed in larger facilities, often spanning multiple buildings, bringing greater efficiency to factories, distribution centres and warehouses.

Factories and warehouses are environments where everything, including the temperature, is closely controlled, of course. Places such as airports present more of a challenge, says David Keene, CEO of Aurrigo. However, even here the shortage of staff created by pandemic-era layoffs has forced airports to overcome the scepticism that you'd expect in such a conservative, highly regulated industry, and embrace the automation of tasks including baggage handling and the transfer of passengers to and from planes.

The biggest unstructured environment of them all is the open road, and there have been huge strides in autonomous driving in recent years. We're probably still at least a decade from seeing fully self-driving cars becoming the norm, says Keene, but it's impressive that many of the big names, such as Waymo, are confident enough to test their vehicles on London's complicated and often-chaotic roads. “Just like a robot Frank Sinatra, if self-driving cars can make it in London and Europe, they can make it anywhere,” he says.

Indeed, the technical challenges have largely been overcome, and regulators are the only major remaining roadblock, says Blake Heimann, a senior associate at WisdomTree. Even a year or two ago, there were very few people who had actually been driven in a Waymo or a Tesla robotaxi. Now, however, many visitors to Austin or San Francisco will have experienced driverless cars, whether that's a regular taxi or one ordered over an Uber. Indeed, China has already found that autonomous vehicles “have a lot fewer accidents and deployment of airbags than conventional cars”, says Bastianpillai.

The rise of robotic surgery

Autonomous vehicles aren't the only area where introducing robots could boost safety, says Bastianpillai. There is already substantial evidence that having surgeons use robots to carry out procedures can lead to better outcomes. Moving to a situation where surgeons sit at a console with two Xbox -type controllers, wearing 3D glasses, means that “a wider range of people can do more procedures a day for much longer”, says Andrew Williamson, a managing partner at Cambridge Innovation Capital (CIC).

This is important as only around a third of young surgeons are able to do the most advanced manual procedures, such as orthoscopic surgery. Even those who do manage to master the advanced techniques typically burn out by the age of 50 because “it's such a strain on the body to contort yourself into different angles to do all of the procedures”. In contrast, even though Williamson has no medical training, it took him just 30 minutes to learn how to use a surgical robot made by CMR Surgical (which CIC has invested in) to sew basic sutures on a training dummy.

Most current systems are set up so that the surgeon sits in the same operating theatre as the patient with the robot alongside them, says Williamson. But it should be relatively simple to move to a “hub-and-spoke model”, where you could have one expert surgeon sitting in Beijing, for example, using robots to carry out surgery in district hospitals out in rural areas. Mark Minevich thinks that predictions that everything will be done by surgical robots within two to three years are somewhat wild, but at some point soon routine procedures are likely to be done by robots under supervision.

Robots in the kitchen

Robotics is even spreading into the service sector, especially in countries such as Japan, says Miyako Urabe, a portfolio manager at the JPMorgan Japanese Investment Trust. You can now walk into a sushi restaurant, finish your meal, pay and walk out without talking to a single human being. You get your own seat assigned by a machine and order on a tablet, the food is delivered on a conveyor belt and finished plates are slipped into a hole next to your seat. Even the food is increasingly produced by robots that “can imitate the craft of the best chefs”.

Many Asian hotels also now make extensive use of robots, says Matteo Borghi, associate professor of entrepreneurship and innovation at Henley Business School. Guests arrive to be greeted by robots in the lobby that provide them with directions and help them check in. Robots are also an increasingly common sight behind the scenes, providing cleaning services and delivering amenities and food to people's rooms. Attempts to run hotels staffed solely by robots have floundered “because people still want the human touch” and European hotels have been more cautious “because they are worried about their reputation”. But the direction of travel is clear “and some hotels are now starting to partner with manufacturers”.

How long will it be before we can all get our own robot maid or butler? Hafner-Cai is relatively cautious, thinking that domestic work and caring will be among the last sectors to see the mass arrival of robots, coming after manufacturing, logistics and even medicine, “due to the safety concerns in interacting with elderly people and small children”. Customer acceptance may be another issue. Measurement technology company Hexagon suggests that, while 63% of adults globally are comfortable interacting with robots in industrial environments, only 46% are comfortable doing so in the home.

Still, it's significant that the key constraint is now “trust, safety and reliability rather than technical capability”, says Omar Moufti, a thematics and sectors product strategist at BlackRock. The Consumer Electronics Show in January showcased a lot of “consumer-focused robots”, notes WisdomTree's Heimann, and although the demonstration models on display still suffered “plenty of hiccups”, they are definitely improving. The first products are starting to hit markets. Unitree is planning to offer its humanoid G1 robot for $16,000, “potentially making it worth the time saved” for high earners who need a helping hand at home. Heimann believes domestic robots could hit the mainstream in as little as five to ten years. We look at the best investments to play the theme in the box below.

How to invest in the robotics revolution

The most direct way to play the robotics revolution is through an exchange-traded fund (ETF), such as the WisdomTree Physical AI, Humanoids and Drones Ucits ETF (LSE: PAIG). This tracks WisdomTree's own proprietary index, which covers what it considers to be the leading companies in four areas: humanoids; drones and autonomous mobility; next-generation factories and logistics; and emerging applications (such as healthcare). The fund is exposed to all parts of the supply chain, from the firms that build the robots, to those that supply key components. The two largest holdings are Ubtech Robotics and Rainbow Robotics, and the ETF has a total expense ratio of 0.45%.

Another option is the iShares Automation & Robotics Ucits ETF (LSE: RBOT), which tracks companies that make robots, alongside software companies and semiconductor firms. The largest holdings include Intel and Terradyne, and the total expense ratio is 0.4%.

Another holding in WisdomTree's ETF is the Korean car company Hyundai Motor Company (Seoul: 005380). Hyundai has ambitious plans to deploy humanoids in their factories over the next few years, says Blake Heimann, and owns robotics company Boston Dynamics. Even today, Hyundai already has “hundreds of welding robots, automated guided vehicles and even robot dogs doing some spot inspections” in its most advanced factories. Hyundai has seen its revenue grow by 80% between 2020 and 2025, but the stock still trades at only ten times 2027 earnings. The yield is 2.3%.

Fanuc (Tokyo: 6954) specialises in precision engineering, industrial robots and automation systems. Its main focus has been traditional static machines anchored to one spot, but it is moving into “co-bots” (robots that collaborate with human workers). It also helps companies develop “smart” factories. The stock trades at 30 times 2027 earnings; this is justified by the fact that its revenue has grown by more than 50% since 2025, with earnings per share doubling during this period. The firm also enjoys large operating margins of around 20% and a return on capital employed of just under 10%, allowing it to generate enough cash to pay a dividend yield of 2%.

A slightly riskier option is Aurrigo International (Aim: AURR). The firm focuses on autonomous vehicles in airports, used especially for baggage and cargo handling. The firm has also developed a software platform that enables people running airports to redesign their operations to take account of developments in automation. The company is currently losing money, but it has already more than doubled revenue between 2020 and 2024. CEO David Keene emphasises that the company is starting to win international recognition and is already working with Changi Airport in Singapore and Cincinnati Airport in the US, with additional interest from Canada and the Persian Gulf.

Richard Clode, co-manager of The Bankers Investment Trust, thinks that companies that design and sell robots won't be the only big winners from the robot revolution. He's very bullish on manufacturing firm Jabil (NYSE: JBL), due to its role in assembling robots and automation technologies. Jabil is currently working with US leading robotics firm Apptronik to help accelerate production of its humanoid robot, Apollo, as well as integrating Apollo into Jabil's own manufacturing processes. Despite seeing its profits more than quadruple between 2020 and 2025, Jabil stock trades at just 18.5 times 2027 earnings.

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There is an old story about a factory that grinds to a halt. Engineers spend days diagnosing the machinery. Eventually, a specialist is called. He walks the floor, listens, taps a single screw, and the plant roars back to life. His invoice reads: one screw tightened, £1. Knowing which screw, £9,999.

That is the investment problem of the moment. The fourth Industrial Revolution is generating enormous noise, almost all of it directed at software, platforms and AI. The golden screw, the thing that actually makes the whole machine run, is somewhere else. It is in the commodites, the materials layer.

The first Industrial Revolution was not won by James Watt. It was won by Matthew Boulton, who provided the capital and the manufacturing base, and by the Darby family, whose coke-fired furnace at Coalbrookdale made the steam engine scalable. The fortunes of the 18th and 19th centuries went to those who owned the feedstock, controlled the refining, and waited for the world to need what they had: Sheffield steel, Coalbrookdale iron, town gas infrastructure, canals. The inventors were celebrated; the owners of the enabling layer were the ones who compounded.

Commodities are where the scarcity lies

We are in the same moment now. The software layer of the fourth Industrial Revolution is commoditising rapidly. The hardware layer, – chips, data centres and power systems – is capital-intensive but replicable. The materials layer is where scarcity lives, scarcity is where pricing power lives, and pricing power is everything in a prolonged stagflationary environment. The golden screws we are focusing on for 2026 are uranium, tungsten, helium and, unfashionably, coal.

Uranium is the foundational fuel of the AI age. Data centres require baseload power that intermittent renewables cannot reliably provide. The global reactor-building programme is accelerating across the US, UK, France, Japan, South Korea, Poland and the UAE. The critical bottleneck is not mining; it is conversion and enrichment.

The Western world's dependence on Russian enrichment capacity is a strategic liability now being addressed at enormous cost, and the opportunity lies across the full value chain – conversion, enrichment, fuel fabrication, and the qualification of non-Russian fuel for Soviet-era reactors across Eastern Europe. The spot price cycle is still early. Term contracts between utilities and producers have only partially repriced.

Why tungsten is today's Sheffield steel

Tungsten has no substitute in its primary applications: cutting tools, armaments, superalloys and semiconductor manufacturing equipment. China controls 80% of global supply and has shown both the willingness and the capability to weaponise that through export restrictions. Western primary production is negligible. Demand from the defence sector is structural and inelastic. Nato's rearmament drives a decade-long demand cycle.

The refining bottleneck, the production of ammonium paratungstate (APT) – the main industrial intermediate and global benchmark for pricing tungsten – is where the real opportunity sits. Western APT capacity is close to zero. Sheffield in the 1780s controlled the world's precision metalworking because it controlled the refining of specialist steels. Tungsten is today's Sheffield steel.

Helium is irreplaceable, non-renewable on any practical timescale, and priced well below its strategic importance. It is essential for MRI machines, semiconductor lithography, rocket propulsion and as a quantum computing coolant. The US government reserve that backstopped global supply for decades is being wound down. Disruption to Russian supplies has already tightened the market. The value lies not in extraction but in the liquefaction and purification infrastructure, the golden screw of the helium value chain, which is nascent, capital-intensive and extremely difficult to replicate quickly.

Coal, particularly metallurgical coal, is the most stigmatised asset in the investment universe and, for that reason, is one of the most interesting. Green steel is real but distant. Blast-furnace steel remains dominant for structural and infrastructure applications through to 2040 at minimum.

Divestment driven by environmental and social governance (ESG) has concentrated ownership among private operators with longer time horizons and lower capital costs, starving the asset class of new supply while demand from India, Southeast Asia and Africa continues to grow. The British parallel is instructive: in the 1780s, coal was the despised fuel of the poor. Within 40 years, it was the foundation of the empire.

The macro context amplifies all of this. We are in a regime where rates stay higher for longer, while the combination of fiscal excess and supply constraints is structurally inflationary, regardless of central banks' intent.

Passive index exposure will not protect capital in this environment. Genuine conviction, expressed with concentration in businesses with pricing power, hard assets or irreplaceable niches, is the correct posture. Private-credit stress, already visible, will accelerate as liquidity mismatches surface. The Yale endowment model, built for a falling-rate, liquidity-abundant world, is not fit for purpose in this one.

Investors who understands this are not making a contrarian bet. They are making the same bet that built the great fortunes of the 18th and 19th centuries – own the feedstock, control the refining, and wait for the world to need what you have.

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Matthew Partridge: James Caan – you founded Alexander Mann and co-founded Humana International, two successful recruitment companies. Would you say that today there's a risk that many university graduates heading into entry-level roles today are being replaced by AI?

James Caan: While I feel much depends on what type of degree the student gains and what they want to do, I do think we're heading for a car crash. I talk to a lot of the big corporate employers, such as Goldman Sachs or KPMG, and if you look at the graduate intake this year, it's going to be less than 50% of the previous year's level.

Up until now, the basic entry-level graduate would have done a research-oriented job. But research is now available at the click of a button, removing the need for someone sitting there for hours trawling through documents and information. Even law firms have significantly reduced their intake, with many of these jobs set to be phased out altogether.

Matthew Partridge: Won't eliminating these entry-level jobs make it harder to find tomorrow's managers and executives?

James Caan: It might, but I think the whole concept of management will change. After all, so much of it is about managing businesses through information, and now access to information, whether financial or operational, is going to be on steroids, both in terms of increased quantity but also accessibility. This, in turn, will drastically reduce the need for managers. What's more, the managers who remain will be much more analytical and data-orientated than today's people-orientated managers.

If you take the three largest recruitment companies in the world, Adecco, Randstad and Manpower, you can see that their share prices have crashed over the last two years. This suggests that the market doesn't believe that the number of jobs they will fill, as well as the fees that they generate, will be anywhere near where they used to be, so my outlook for the job market is very bearish.

Matthew Partridge: So what sort of degrees should students looking to get a job after university do?

James Caan: Unless they want to follow a specific path, such as medicine, I don't think it is possible to generalise. However, I would say that degrees involving learning to work with data, whether through physics, maths or science, are going to be much more valuable. It is also important to realise that education is about more than just getting a degree; it's about capability, confidence and critical thinking. I left school at 16 because I wanted to get on with building something. Later, I went to Harvard because I wanted to sharpen what I had learned through experience. Both experiences were “education”. At the very least, the career departments of universities and schools need to reflect the careers of today with the advice they give students.

Matthew Partridge: You've been vocal about the need for change in the education system through your work with the Foundation for Education Development (FED). What sort of reforms would you like to see?

James Caan: Education is a very sensitive subject for me because I feel passionately that the UK's education system has not kept up with the times, with students that are coming out of schools ill-equipped for the jobs that exist today. The key problem is that the education system dates back to the 1950s idea of GCSEs and A-levels leading on to university, even though the economy has changed dramatically over that period. The problem is made even worse by the fact that many teachers working today were trained 25 years ago, which means key aspects of their skill sets can't meet the needs of today's students.

When I talked to various people about incorporating technologies such as AI or animation into classrooms, they all say “It's a great idea, James, but we don't have the resources within the education system to deliver those courses because the teachers are just not equipped”. What is particularly worrying is that the [Persian] Gulf and China are way ahead of us in terms of using AI and technology to provide advanced education at schools and universities, and their offerings are starting to overtake what's available in our institutions. Even Oxford, Cambridge and the LSE are falling behind, which means that they, and the country, could lose their income from overseas students.

Matthew Partridge: Is the solution to bring more money into education, or change the way in which education is delivered?

James Caan: The discussion has shifted towards skills, apprenticeships and employability, not just academic routes. The decision to refocus public funding away from master's-level apprenticeships is a clear signal of intent: prioritise earlier-stage, broader access to training. We also need to deliver lessons better. Thanks to AI, even when the teacher isn't qualified to deliver a topic, you can now design bespoke courses, using content culled from world-class institutions, which can then be delivered by virtual avatars.

So, for instance, I've always been a big fan of teaching students the basics of personal finance, such as owning a credit card and opening a bank account, right through to the mechanics of setting up a company and issues such as limited liability. Yet when I've raised the issue, the big objection has always been that many of those teaching in schools today don't know that much about those topics either.

The good news, though, is that thanks to the explosion in information, there's so much content available that it should be relatively easy to design a course and program an avatar to deliver a lesson for 30 minutes, with the teacher dealing with any further questions that the pupils might have. While this might seem futuristic, I'm already seeing schools in the Gulf and China using such technology in this way.

Matthew Partridge: You were a presenter on Dragons' Den, a TV programme credited with promoting entrepreneurship. Do you think that we're becoming more entrepreneurial as a society?

James Caan: Dragons' Den did something very powerful. It normalised entrepreneurship. It showed people from all backgrounds that starting a business was not reserved for a particular class, education or network. It made business conversations part of mainstream culture. That visibility matters enormously because you cannot aspire to what you cannot see.

Historically, we have had a cautious culture. We are more comfortable with security than risk. To fail in business still carries a stigma here that it does not in the US or the Middle East. But this is changing. Younger generations are far more comfortable with enterprise, side businesses, and alternative career paths. The cultural shift is happening, but the system has not yet caught up with the ambition.

Matthew Partridge: A big criticism of British entrepreneurship is that those who do set up companies still focus more on selling themselves to larger groups than growing into global champions. Is this true, and if so, what are the reasons for it?

James Caan: There is a lot of truth in that. Access to sufficient capital to achieve scale in the UK is still more limited than in the US. Founders receive acquisition offers earlier than they should, and without the right support, selling can feel like the rational decision. But I also think Britain can change this if it gets serious about confidence and long-term growth. When sentiment improves, companies invest more, and founders hold their nerve. The January business readings show we are not there yet, but the direction matters.

We need patient capital, better advisory systems, and a culture that celebrates building enduring companies, not just quick exits. A great example of the sort of thinking required is Amazon. At present many listed firms think in quarterly cycles because they have to report every three months and therefore the time horizon for investment is very short. However, Amazon held fast to its view that they needed to invest in order to build a world-class platform that would make them and their investors' a lot of money. While this meant that Amazon received a ton of negative press until the platform was built, it quickly became one of the most successful firms in the world, showing the benefits of thinking a bit more longer term.

Matthew Partridge: The government has recently talked about trying to reduce the amount of red tape around business. Do you think that will work?

James Caan: Yes, we definitely need to reduce red tape. I mean, try opening a bank account tomorrow or getting a VAT or PAYE number. One of the companies I set up recently took five months to get a VAT number. It's just ridiculous. And the awful thing is that, with all today's technology, we should be able to do this online. How is it that I go to Barclays and it can take me four months to open an account, but I can open one with a fintech such as Revolut in ten minutes?

Some of the decisions that the government has taken haven't helped. The decision to hike national insurance was particularly ill-thought through; it looks as though the Treasury may end up losing money because of the reduced number of hires. Similarly, the tax hikes on some of the wealthy have resulted in people leaving the country. I don't think that the government understands how to implement policies to boost business and entrepreneurship.

Of course, I'm not against all tax rises, especially if they are used to fund retraining for workers displaced by AI. It might make sense to target the huge technology companies that are causing all the problems. However, by hiking employers' national insurance contributions to 15%, the only thing that you are going to do is to kill all the small companies.

James Caan CBE is the founder and CEO of private-equity firm Hamilton Bradshaw as well as chairman of both Recruitment Entrepreneur and Ingenia Global Partners. Between 2007 and 2012, he was on the panel of Dragons' Den. He has written four books on business.

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Anybody who has watched the Dune films without having read the books may be confused by why an obviously high-tech space-faring future civilisation appears to have no computers. The in-universe explanation is simple: humanity had developed forms of artificial intelligence, but these machines and a small elite came to control the rest of humanity. All computers were eventually destroyed in a long, semi-religious revolt and the creation of all forms of “thinking machines” was banned from then on.

It is becoming hard not to imagine this when speculating about how AI will change the world. After all, if AI will soon do everything that its most excited proponents claim, the potential for huge job losses, the economic consequences of mass unemployment, and the broader lack of purpose and autonomy sound like exactly the kind of conditions to create mass unrest. That doesn't mean that a real-world equivalent of Dune's Butlerian Jihad would be successful in suppressing the use of AI – the Luddites did not manage to stop the industrial revolution – but the potential for social strife is there.

Yet if AI does not result in huge economic changes, it is questionable whether all the capital being pumped into the sector will pay off. There seems little doubt that AI research will be hugely significant in some areas, but that doesn't mean it will transform work more widely. We may end up with a lot more middle-management jobs supervising and fixing the output of AI tools. This could create its own problems – how do young workers gain skills and expertise if the basic work on which they learn is done by AI? – implying that long-term end-to-end productivity gains could be surprisingly scarce.

Hard assets take over from ‘capital-light’ stocks

At the moment, I have no firm view on which way this goes or whether we find a genuinely useful middle course. However, it is clear that investors are increasingly concerned that many knowledge-based activities are potentially at risk from AI. Hence they are rotating away from these stocks towards those with businesses that are rooted in the physical world. You can understand the logic: it is difficult, for example, to replace a railway with a large language model.

There are other trends supporting this. AI disruption is clearly driving attention in real assets, but it also sits alongside a wider set of pressures that includes defence and security, energy needs and healthcare demand, as the team at Ruffer Investment Company (LSE: RICA) points out. This is an environment in which it becomes attractive to own “constrained sources of supply” such as commodity equities, as a hedge against inflation and other shocks.

More broadly, a shift to firms with hard assets is very different to the consensus that has prevailed for well over a decade. Investors have come to see asset-light stocks with low capital expenditure as safer and more desirable. This remains purely speculation at this stage, but maybe a tense, volatile world with a focus on security means that old-fashioned heavy industries will be the darlings of the next cycle.

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On the face of it, Taiwan seems an unlikely location for a tech superpower as it is a small island with a population that is not even half that of Britain’s.

But “just as some small countries have managed to dominate a single sport, such as New Zealand in rugby, Taiwan and its companies have managed to dominate semiconductors and manufacturing”, says Isaac Thong, lead manager of the Aberdeen Asian Income Fund.

The demand for chips created by the AI boom has caused Taiwan’s exports to the US “to grow by more than 150% in the year to January, putting it on a par with China” as an export powerhouse, says Iain Barnes, chief investment officer of Netwealth. This has led to soaring share prices. Taiwan’s stock exchange is now one of the largest (by market capitalisation) in Asia.

Taiwan’s tech miracle

Taiwan’s success “is essentially a story about what a huge investment in science and technology can do for a country over a period of time”, says Chetan Sehgal, the lead portfolio manager at Templeton Emerging Markets Investment Trust.

The initial impetus for Taiwan’s development came from the state, says Usha Haley, director of the centre for international business advancement at Wichita State University.

The country’s industrial policy promoted development “through export promotion policies, land reform and state-backed research, and development institutions such as the Industrial Technology Research Institute, all of which encouraged small and medium-sized companies to gain technical mastery”.

From that early start, Taiwan later benefited from two strokes of luck. The first was its physical proximity to China, which meant that when China started to open up its economy in the 1980s and 1990s, Taiwanese entrepreneurs, with their high level of education, ready access to capital and knowledge of Chinese, were able to serve as a bridge between the US and China, says Sehgal.

This involved setting up factories in China and Taiwanese companies providing “technological solutions for the problems that China’s growing manufacturing sector faced”.

That mainly involved components to start with, but over time this expanded to include sophisticated electronic chips.

The second stroke of luck was that at the same time as Taiwan was benefiting from China’s move towards a market economy, Japan had a major falling out with the US, says Chris Chan, a portfolio manager at EFG Asset Management.

The US was unhappy that Japan was using tariffs to give its then globally dominant semiconductor industry an unfair advantage. The resulting trade war gave Taiwanese firms, which enjoyed a much more open trade relationship with the US, a major advantage, allowing them “to build up Taiwan’s chip industry to the point where it became the major chip supplier to the rest of the world”.

The rapid growth of Taiwan’s technology sector has produced a virtuous cycle, where the physical proximity of a large number of technology firms has allowed the creation of a self-reinforcing tech “ecosystem” that Steve Brotman, founder of Alpha Partners, compares to Silicon Valley in the US.

Today, “you have these industrial parks where all the main tech firms are located together, so they can walk across the road to have a coffee with their main customer, or lunch with their main supplier”, says Chan.

This enables Taiwanese tech firms to work together and anticipate each other’s needs, helping keeping costs down so they can stay ahead of rivals in the rest of the world.

Taiwan still retains a culture and education system that values science and technology, and that is vital, says Chan. “It’s not like the US or Europe, where many of the top university students want to go into law or investment banking.”

Instead, those graduating from college in Taiwan want to work for companies such as TSMC, as the status acquired from working in technology or engineering “is still incredibly powerful, probably more than in any country I have been in”.

The secret of TSMC’s success

At the core of Taiwan’s technology sector is a single company, Taiwan Semiconductor Manufacturing Company (TSMC). It is so important to the Taiwanese stockmarket that it accounts for just over 40% of the Taiwan Stock Exchange (and just over half of indices such as MSCI Taiwan).

Lucy Smith, senior investment manager at Killik & Co, points out that this is more than the entire Magnificent Seven (Alphabet, Amazon, Apple, Tesla, Meta Platforms, Microsoft, and Nvidia), which account for 35% of the S&P 500. So a lot of the Taiwanese stockmarket “is driven primarily by just one company’s performance”.

TSMC’s dominance stems from the decision of Intel, which essentially created the industry under co-founder Gordon Moore, to “try to do everything itself, from chip design to fabrication, without any outside help”, says Thong. By contrast, TSMC decided that it would specialise in just one part of the process, the actual making of the chips. Thanks to its reputation for protecting the details of each of the chipmakers it works for, it built a reputation for large-scale reliable manufacturing, “attracting business from companies that wouldn’t work with Intel because they didn’t want to risk losing their intellectual property”.

The wisdom of TSMC’s focus on manufacturing has become apparent in recent years, as it has allowed it to make money from manufacturing the graphical processing units (GPUs) that have become so important to the present-day computer industry, says Brotman.

Intel viewed GPUs as a “sideshow, only of interest to those playing computer games”, but TSMC was happy to help Intel’s rivals fill the gap.

This proved wise, as demand for these specialised chips has boomed, initially from those mining bitcoin, then from AI, which needs powerful chips to work.

No company remains dominant forever, of course, and TSMC could end up going the way of Intel, either because of a shift in technology – towards quantum computing, for example – or because the economics of the chip industry itself changes, says Brotman.

During the dotcom era, many telecoms companies briefly became Wall Street darlings as they could make a lot of money from building fibre-optic cables, only for the fibre business then to become commoditised. Yet it’s hard to see computer chips being supplanted in the near future.

Brotman expects a “proliferation” of providers and manufactures of chips over the next ten to 20 years – plenty of time for TSMC to make lots of money.

Indeed, “TSMC’s technology position has only got stronger in the last few years”, says Abbas Barkhordar, a portfolio manager at the Schroder AsiaPacific Fund. No other company is spending close to the amount that TSMC is on research and development and the gap between TSMC and the only two firms that could plausibly be its rivals, Intel in the US and Samsung in Korea, “is only getting wider”.

Intel “is struggling in implementing its technological road map” and Samsung is cutting back its foundry business “as it hasn’t made Samsung as much money as it expected” it to.

It’s not all about the tech

Taiwan’s stockmarket and wider economy may be dominated by technology, but there are several other areas where it boasts globally competitive firms, says Alex Holmes, a regional director at the Economist Intelligence Unit.

Taiwan is particularly strong in consumer goods, ranging from relatively niche speciality goods, such as “bubble tea”, which is popular across Asia as well as in the US and Europe, to some world-leading companies in “activewear”.

Taiwan also has a flourishing precision machine-tools industry, which produces equipment that is widely used in automated factories in the US and Europe.

Just as Taiwan’s technology sector has been able to expand outside its small domestic market, so many Taiwanese firms in other sectors have pulled off a similar trick, says Sehgal.

“If you’re an avid cyclist you’ll know that the top two brands in the world are actually owned by Taiwanese companies: Giant and Merida.”

Taiwan also has a large medical drug industry, “with quite a few innovative biotechnology companies, some of which have come up with some interesting treatments that have been able to win approval from the Food and Drug Administration”, the US regulator.

Indeed, the country has a large (and growing) number of companies that have “strong brand equity and vertical integration”, agrees Haley. Such companies “reward patient, research-oriented investors rather than momentum traders swept up by narratives about a booming market”.

And although Asian companies may have a bad reputation for not being transparent, as well as for favouring insiders over investors, “Taiwan is unique in that the quality of its corporate governance is very high”, says Sehgal. Barkhordar agrees. In his view, Taiwanese firms “tick all the boxes that you’d like to see as an investor”.

They “have a great focus on capital allocation, a really good record of looking after minority and foreign shareholders and generally have good shareholder returns as well”.

The geopolitical risks are overstated

Any discussion of Taiwan has to reckon with the geopolitical risks associated with a potential conflict with China, which has always considered Taiwan to be a rogue province.

However, the chances of any direct action by Beijing within the next decade are “very low”, says Chan. “What’s happened to Russia in Ukraine will be at the forefront of the Chinese leadership’s minds”, especially given the fact that, as an island nation, Taiwan would logistically be much more difficult for China to attack than Ukraine was for Russia.

Even if China did manage to overcome the military challenges, the fallout of any attack could be disastrous for China’s economic strategy, says Chan. At the moment, China’s weak domestic economy and failing property market make it more dependent than ever on exports, most of which are carried by sea.

So if Japan, the Philippines and the US responded to an attack on Taiwan by blockading China, it could cut this sea-borne trade off at a stroke, as well as depriving it of key resources such as oil.

Invading Taiwan would almost certainly cause foreign investors to sell Chinese assets, which would cause Chinese renminbi to crash.

This in turn would be a major blow for the Chinese leadership’s dream of the renminbi replacing the dollar as the global reserve currency.

Thong agrees, seeing military action as very unlikely in the short run, with some sort of diplomatic agreement that preserves de facto Taiwanese autonomy the most probable outcome in the long term.

For one thing, a Chinese invasion would inevitably involve the destruction of the very chip plants that China needs to manufacture most of the electronic goods it produces.

Beijing is trying to develop its own chip industry to make it less dependent on Taiwan, but this is going to take some time to have an impact, “as you don’t just need machinery, tools and equipment, but also the people, know-how and experience”.

As a result, companies such as Huawei are still struggling to produce high-end chips at scale in an efficient enough manner to challenge Taiwan’s supremacy.

China isn’t, of course, the only country attempting to create its own chip-manufacturing capacity. TSMC is relocating some of its production to the US, in response to pressure from the Trump administration. But the lack of expertise and shortage of qualified engineers there means that “a TSMC plant in the US will have 30%-40% higher operating costs and will require 30%-40% higher capital spending costs than a comparable plant in Taiwan”, says Chan.

When TSMC and other Taiwanese firms do move factories outside of Taiwan to places such as Mexico and Thailand, “it tends to be the lower-end products, with the high-value work remaining in Taiwan”.

All this suggests that the clustering of high-end manufacturing that is so central to the success of Taiwan’s tech sector won’t be under threat in the foreseeable future.

In any case, the more Taiwanese firms relocate their production overseas, the lower their geopolitical risk, says Chan. “Investing in Taiwan is a less risky bet than it was perhaps five or ten years ago in terms of the physical concentration of factories actually in Taiwan.”

Investing in Taiwan: the best stocks to buy now

Perhaps the easiest way to invest in the Taiwanese stockmarket is through an exchange-traded fund, such as the iShares MSCI Taiwan UCITS ETF (LSE: ITWN).

This invests in the MSCI 20/35 Taiwan index, which covers 87 large- and medium-cap Taiwanese shares, accounting for around 85% of the market. It is structured so that the largest holding is capped at 35% of the index and all other holdings at 20%.

TSMC thus accounts for just over a third of the portfolio, compared with more than half of the MSCI Taiwan index. The average price/earnings ratio is 22.9, the yield 1.38% and the total expense ratio 0.74.

TSMC (Taipei: 2330) is the world leader in manufacturing computer chips. Thanks to the AI boom, it begins the year “in a position that few industrial companies ever reach: simultaneously capacity-constrained, margin-expanding and structurally indispensable”, says Saurav Sen of Gimme Credit.

But despite the boom, TSMC’s capital allocation is disciplined, with a return on capital employed of nearly 30%, despite attempts geographically to diversify production outside of Taiwan. Revenue has nearly tripled between 2020 and 2025, more than justifying the fact that the stock trades at 21 times expected 2027 earnings.

One company that has benefited from TSMC’s success is ASE Technology Holding Co (Taipei: 3711). ASE has developed a profitable niche packaging and testing the chips that come out of TSMC’s foundry.

Isaac Thong of Aberdeen Asian Income Fund likes the fact that the firm has a reputation for “timeliness as well as being trustworthy and producing high-quality work”. Between 2020 and 2025, ASE has grown its sales by around 40%, while increasing its earnings per share by a similar amount. The shares trade at 17.4 times expected 2027 earnings and offer a dividend yield of 2.42%.

Another Taiwanese tech company that has a good relationship with TSMC is MediaTek (Taipei: 2454). At the moment it specialises in producing the blueprints for the chips used in low-end smartphones.

This strategy has proved successful, with sales more than doubling between 2019 and 2024, alongside high returns on capital. Thong particularly likes the fact that MediaTek is now making big strides towards entering the high-end computer-chip market, especially in relation to chips used by data centres, which have a much better growth potential. The shares trades at 28.5 times projected 2026 earnings.

Delta Electronics’ (Taipei: 2308) has a leading position in power-management and thermal technologies, which will benefit from the explosion in demand for servers for artificial intelligence, which need to be cooled, reckons Morton Lo, chief analyst, APAC, at global broker FXTM.

Already, Delta’s revenue has grown by around 55% between 2019 and 2024, with earnings per share rising by 63% during the same period. While the stock trades at 63 times trailing earnings, strong growth means that this is expected to fall to a much more reasonable 36 times earnings in 2027.

One example of a thriving Taiwanese company that has achieved global success outside of the technology sector is Eclat Textile Company (Taipei: 1476). It is one of the world’s largest manufacturers of high-end sports clothes, making items for well-known brands such as Lululemon and Nike.

It has seen its revenue grow by just under 30% between 2019 and 2024, with earnings per share increasing by more than half during the same period. At the same time, it has been winning awards for sustainability. The stock trades at 17.8 times expected 2026 earnings, and offers a solid dividend yield of 3.8%.

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How bad are the youth unemployment figures?

Youth unemployment figures make grim reading. Government data released earlier this month shows that the UK unemployment rate rose to 5.2% in January – the highest rate for five years.

But in the last quarter of 2025, the unemployment rate for 16-to 24-year-olds rose to 16.1%.

That’s higher than the Covid peak of 15.3% in late 2020 and the highest level for more than a decade. And for the youngest workers –16-and 17-year-olds who have left education – the rate is a shocking 34.2%.

Whatever measure you look at, there’s clear evidence that younger workers are bearing the brunt of the UK’s increasingly soft jobs market.

For example, the number of payrolled employees in the UK fell by 134,000 in the year to January. But for younger employees (on this metric meaning younger than 34), the decrease was 174,000; for older workers there was a net increase.

How does this compare globally?

It’s bad. For the whole of this century, it’s been easier for young workers to find employment in the UK than in mainland Europe, hence the millions of young Europeans who made Britain their home.

But now, for the first time that situation has reversed. According to the OECD think tank, the UK’s youth unemployment rate now stands at 15.3% – higher than the EU’s level of 15% and more than twice that of Germany.

Yet for workers overall, the jobless rate remains higher in the EU than here, at more than 6%. It’s only for younger workers that Britons are worse off.

What’s gone wrong?

A mix of macro-economic factors, made worse by recent policy decisions by the Labour government.

Youth unemployment has been a persistent and cyclical part of the UK labour market over many decades.

Structural shifts in the post-war period, deindustrialisation in the 1980s and the global financial crisis – all saw youth unemployment rise, and it has consistently been higher than overall employment.

Recent years have seen a long period of low or no growth and lacklustre productivity, combined with an inflationary spike and cost pressures on businesses.

All of that tends to reduce hiring and young workers are often the first affected.

However, there’s no doubt that Labour has made things worse. And that’s not merely the judgement of Labour’s opponents: it’s the publicly expressed view of Huw Pill, the Bank of England’s chief economist.

What does the Bank of England’s chief economist say?

Huw Pill told a parliamentary committee this week that last year’s increase in employers’ national-insurance contributions, plus the drive to level up the youth rates of the minimum wage towards the main adult rate, “have had a particular effect on young people” aged between 16 and 21.

This cohort of young people were already launching their careers at a difficult time in the aftermath of the pandemic, he says, and in the face of deeper structural changes such as the adoption of AI that policymakers might find “difficult to manage”.

What about the minimum wage?

The minimum wage has surged by 75% – in real terms, not merely nominal – since it was introduced by New Labour in 1999.

Initially, the rates were £3.60 per hour for the over-22s and £3 per hour for 18-to 21-year-olds.

With inflation, those rates today would be £7 and £5.80. In fact, the minimum wage is now £12.21 per hour for the over-21s (rising to £12.71 in April); £10 per hour for 18-to 20-year-olds (rising to £10.85); and £7.55 for 16-to 17-year-olds (rising to £8).

The policy was widely accepted as a success and adopted by the Conservatives, who had opposed it at the time as a jobs-destroyer.

And indeed, since its introduction there has been little sign that it was hurting employment; in 2022 the headline joblessness rate hit its lowest since the 1970s, at 3.6%.

So what happened?

The Conservatives became so confident about the policy that in government they set a goal of raising the main minimum wage (rechristened the “living wage”) to two-thirds of median earnings, making it one of the highest relative to earnings in Europe.

They also phased out lower rates for workers aged 23-24 in 2021 and for 21-to 22-year-olds in 2024.

Yet it’s now clear that the inexorable rise of the minimum wage has reached a tipping point, with businesses loudly telling policymakers that it is stopping them from hiring young workers.

Nor is it solely minimum-wage workers who are struggling: it’s graduates, too.

The soft economy, combined with the promise of AI’s workplace abilities, has led to a graduate “jobpocalypse” in which companies have slashed or paused recruitment programmes, entry-level jobs are disappearing and graduate-level unemployment is at an all-time high.

Why is this issue so important?

Because people’s early interactions with the labour market play a critical role in shaping their long-term futures.

Researchers have consistently found that NEETs – people not in education, employment or training – are “at risk of life-long socio-economic scarring, remaining at significantly elevated risk for worklessness and health problems for decades”, says John Burn-Murdoch in the Financial Times.

In the UK, this group of young people who are increasingly disengaged from not only the economy, but also the rest of society, has doubled in just over a decade from 4.5%-9% of those aged 20-24.

Alan Milburn, the Blair-era cabinet minister, is now conducting an inquiry into the issue.

“We’re seeing something dramatic changing in the labour markets,” says Milburn.

Some 45% of 24-year-olds who are not in education, employment or training have never had a job.

"If you haven’t had a job by 24, that entails a long-term scarring effect and you’re probably then stuck in a lifetime on benefits.”

Britain is “facing the existential risk of a lost generation” – with all the economic and fiscal damage, and social and political turbulence, that will entail.

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This time last year, FTSE 100 data and analytics group Relx (LSE: REL) was flying high as investors bought into the company’s AI growth story.

One year later and sentiment has changed. Shares in the blue-chip business have fallen by around 40% over the past 12 months, making the business one of the worst-performing stocks in the FTSE 100.

According to the company, it spends around $2 billion every year developing its proprietary AI technology, putting it among the biggest UK-based investors in AI.

However, Relx has missed out on the recent global rally in AI stocks. It has underperformed the Global X Artificial Intelligence & Technology ETF by 70% over the past 12 months.

Investors have soured on the company due to concerns that it’s losing its edge.

The firm’s value fell by as much as 15% in a single day in early February after Anthropic, the maker of Claude AI, launched a suite of 11 agentic AI plug-ins to automate various tasks.

One of these is a tool targeted at in-house legal teams and academic researchers, which can review documents, flag risks and track compliance, a direct competitor to Relx’s fastest-growing product, LexisNexis.

The new product has the potential to gut this key business and democratise legal services. That’s the theoretical outlook for sales, anyway. In reality, there’s a lot more to consider.

Relx has a key advantage in data

“Clean” data is the biggest issue. AI currently struggles to work with data that isn’t in the correct format. Relx’s LexisNexis division develops and sells legal analytics and generative AI products built and trained on its exclusive legal content – one of the largest repositories of accurate legal content in the world.

The bulk of this content concerns English common law, a dominant force in global commerce that governs approximately 40% of international business and financial transactions.

English common law has been developed through judicial decisions (precedent) alongside statutes, but the majority of the case documents underpinning common law are not publicly available.

LexisNexis has spent decades acquiring, cleaning and feeding this data into its models. It hosts over 161 billion legal and news documents and records, and adds 1.6 million new documents a day. It claims to process 38 million legal documents a day.

Of the 12,000 staff employed by the group, roughly half are engaged in cleaning, managing, processing and developing data. And Relx has already announced or launched 13 products driven by generative AI. Revenue growth at LexisNexis has risen from 2% to 9% over the past six years, driven by products such as Lexis+ AI and its Protégé product. Lexis+ AI was the first AI tool rolled out in US law schools.

This isn’t just a competitive advantage. Relx’s data advantage is one-of-a-kind.

The only way a company such as Anthropic would be able to get its hands on the data that Relx has spent decades accumulating would be to buy the business.

Initial indications suggest users have already discovered the drawbacks of Anthropic’s tools. Users have cited sloppy or made-up results based on freely available data hosted on sites such as Wikipedia.

So it looks as if the market has overreacted to the potential competitive threat of Anthropic’s new AI tools. Relx still has the structural advantage. Growth may take a short-term hit as investors try out other tools, but Relx will ultimately remain the single best and most reliable source for the world’s leading legal minds.

Relx’s legal business accounts for around a fifth of group revenue.

Its biggest divisions are its risk-management arm, which accounts for around 40% of revenue, and its scientific, technical and medical (STM) business, which accounts for around 30% of revenue. One of Relx’s best-known brands includes ScienceDirect, the world’s largest scientific and medical database.

All of these core businesses operate around the same framework.

The company has a bespoke proprietary dataset that helps its customers make better decisions and produce trusted research.

AI is actually helping the STM business rather than hindering it. Academics and publishers have reported an explosion in so-called “AI slop” making its way into scientific papers, with some figures suggesting as much as 50% of published content is now co-authored by AI.

This means it’s now more important than ever for scientists and researchers to know the source of their research. That’s especially true in industries such as biotechnology, where the outcome of the paper can literally involve the difference between life or death.

This is only going to reinforce the need for trusted data repositories.

Expect steady growth from Relx

Last year, Relx’s revenue grew 7% while adjusted operating profit ticked up 9% to £3.3bn.

Earnings per share rose 10% thanks to a £2.5 billion share buyback, £1.5 billion of which was executed last year. And while the world’s leading AI players, such as ChatGPT’s owner OpenAI, devour cash, Relx reported cash flow of £3.3 billion in 2015 with a cashflow conversion rate of 99%.

The company’s cash generation underpins its dividend, which increased 7% last year to 67.5p, and its share buyback, as well as selective acquisitions.

Last year, the company completed five small acquisitions for a total consideration of £270 million. Following the results, analysts at Investec slapped a “Buy” rating on the shares, noting the company’s expanding competitive advantage in the sector.

With the stock trading at a forward price-to-earnings (p/e) ratio of around 19, compared with its five-year average of 29.5, now could be the time to snap up this data giant’s shares while the market is looking the other way.

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A few years ago, Dario Amodei “was just another techie in San Francisco”, toiling in relative anonymity and playing video games on Sunday nights with his sister Daniela.

Fast forward to 2026, says The Sunday Times, and the Anthropic co-founder is worth billions.

He runs ones of the fastest-growing and most potentially disruptive companies in the history of capitalism, flits around the world and writes lengthy papers highlighting the dangers of untrammelled AI.

Unfortunately, he also finds himself in the crosshairs of the Pentagon under Donald Trump.

In a showdown this week, Amodei was summoned to meet secretary of war Pete Hegseth.

Hegseth gave Amodei an ultimatum. If Anthropic refuses to give the Pentagon free rein on the use of its Claude AI software “for all lawful purposes”, his firm faces penalties far beyond the cancellation of its $200 million contract.

It will be deemed “a supply-chain risk” – a move usually reserved for foreign companies from dubious regimes – forcing any other firm with military contacts to ditch its software.

It might also be compelled to do national-security work under the Defence Production Act.

Trump has been branding Anthropic dangerously “woke” and “ideological” for months.

It’s fair to say that “Amodei’s outspokenness and sharp elbows have earned him both respect and derision”, says Alex Kantrowitz on Medium.

A top-level research director at OpenAI who broke ranks to form Anthropic with his sister in 2021, he has long split opinion in the Valley.

Admirers see a “technological visionary” and “a safety-minded leader”. Critics charge that he is a wolf in sheep’s clothing – a “control-oriented ‘doomer’ who wants to slow AI progress” – the better to “shape it to his liking and shut out the competition”.

Born in San Francisco in 1983, Amodei became an activist early on. As an undergraduate at Caltech he protested against the Iraq war, railing against fellow students for their “passivity”.

The death of his father in 2006 after a long rare illness had a big impact and he shifted his graduate studies at Princeton from theoretical physics to biology in the hopes of decoding human illness.

A later move into research, studying proteins in and around tumours, prompted his first experimentations with “machine learning”, as it was then known. “The complexity of the underlying problems felt like it was beyond human scale,” he later said. He realised tech could bridge the gap.

Dario Amodei's move into business

Amodei left academia to pursue AI advancement in the corporate world, where there was cash to support it – joining the Chinese search engine Baidu and then, briefly, Google Brain. He was “among the earliest employees of OpenAI”, says the Financial Times, and instrumental in developing the large language models behind ChatGPT.

He left five years later after disagreements with Sam Altman over OpenAI’s direction and “with concerns about AI’s potential for harm if appropriate guardrails were not put in place”.

From the get-go, the company’s mission was simple, says Kantrowitz – build LLMs and “implement safe practices to pressure others to follow”. When the Claude chatbot was released in 2023, it won high acclaim for its “high-EQ personality”.

Meanwhile, Amodei grappled with ethics – and found himself increasingly landing on the side of pragmatism. “Unfortunately,” he wrote, “I think ‘No bad person should ever benefit from our success’ is a pretty difficult principle to run a business on.”

With a float scheduled this year likely to value Anthropic well north of $300 billion, Amodei already has a lot on his plate. The Pentagon stand-off will add to the stress. “They say your values aren’t truly your values until they cost you something,” says Bloomberg. Dario Amodei is about to be tested.

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One of the major headlines when Tesla announced its Q4 results in January was the surprise announcement that it would wind down production of two of its flagship car products, in order to free up more resources to produce robots.

“We are going to take the Model S and X production space in our Fremont factory and convert that into an Optimus factory,” said Tesla’s CEO Elon Musk in a call with industry analysts following the earnings release. “That is slightly sad, but it is time to bring the S and X programs to an end and shift to an autonomous future.”

This underscored not only a strategic pivot that Tesla (NASDAQ:TSLA) has been envisaging for years, especially since the launch of its robotaxi in Austin, Texas last year, but the rapid emergence within the tech industry of what is increasingly being dubbed ‘physical artificial intelligence (AI)’.

Physical AI, in essence, is the incorporation of AI into physical objects. The clearest illustrative examples are things like self-driving cars or sophisticated robots, but there are numerous other examples such as drones and smart warehouses.

“Physical AI is not a single industry but a fast-emerging ecosystem where intelligence is being embedded into machines that operate in the real economy,” said Pierre Debru, head of research, Europe at asset manager WisdomTree.

Humanoid robots like Tesla’s Optimus, or the Walker S2 (an industrial humanoid robot that knows when its own battery is running out of charge and can replace it itself autonomously) from Chinese rival Ubtech Robotics (HK:9880), mark an eye-catching evolution from earlier forms of robot which, while undoubtedly valuable in factory automation, don’t quite step into the realms of science fiction.

Developments in physical AI

Self-driving cars are one of the most tangible aspects of physical AI, particularly for residents of cities like Austin or Los Angeles where they already roam the roads.

But self-driving cars could become a reality in the UK too by the end of the year. The Automated Vehicles Act means that automated vehicles will be legally permitted on UK roads this year.

Waymo, Alphabet’s (NASDAQ:GOOGL) self-driving car arm, is launching a pilot service in April.

Another much-vaunted example of physical AI in practice is the increasing efficacy of robotic surgeons.

Tools like Da Vinci, from Intuitive Surgical (NASDAQ:ISRG), enable surgeons to perform robot-assisted operations with greater precision, and potentially remotely. Advances in haptic technology mean that the latest generation of the Da Vinci robot can sense the amount of force being applied to tissue during surgery, effectively simulating a human surgeon’s sense of touch.

According to Intuitive Surgical, over 20 million people have now had surgery performed with the help of Da Vinci robots.

How to invest in physical AI

If you’re looking to invest in physical AI, it pays to consider the entire ecosystem as well as the specialist companies that have been mentioned in this article.

Nvidia’s (NASDAQ:NVDA) CEO Jensen Huang could be argued to have popularised the phrase ‘physical AI’ and Nvidia’s Cosmos is one of the leading platforms for physical AI, so it is a good place to start as a ‘picks and shovels’ play.

Similarly, the machine learning systems that enable physical AI to improve through experience are developed by some of big tech’s other major players. Alphabet’s Gemini, for example, is the large language model underpinning the next generation of Atlas robots from Boston Dynamics.

Alphabet is also a decent AI play given its ownership of self-driving car company Waymo.

You might want to invest in physical AI via an exchange-traded fund (ETF), as this will give you diversified exposure to companies in the industry.

On 19 February, WisdomTree launched the Physical AI, Humanoids and Drones UCITS ETF (LON:PAIG). It is Europe’s first ETF to focus specifically on physical AI. Top holdings include Ubtech, South Korean robotics firm Rainbow Robotics (KOSDAQ:277810) and Nvidia.

While PAIG is the first pure-play physical AI ETF in Europe, there are other pre-existing options with a similar if slightly broader focus. The ARK Artificial Intelligence & Robotics UCITS ETF (LON:ARCI) holds some non-physical AI companies but also has a significant exposure to physical AI and robotics companies like Tesla and Teradyne (NASDAQ:TER).

The last couple of weeks have been confusing. Mega-cap tech stocks and other firms involved in the AI boom have been hit because investors are suddenly more worried about how much money they are spending and whether it will earn a decent rate of return.

At the same time, a broad swath of firms that might potentially be disrupted by AI have also been knocked down.

This is not entirely inconsistent: you can set out a scenario in which AI is revolutionary, but early investors are not rewarded for their prescience because too much money was spent too fast.

This has happened in previous revolutions: the British railway boom of the 1840s – one of the greatest investment manias of all time – made the stagecoach extinct yet also bankrupted many early backers. But it’s hard to discern such a thesis behind the recent moves.

Rather, it feels as if investors are increasingly unsure who will be the winners and losers of the AI boom. That’s fair: anybody who feels too certain is dangerously overconfident.

My instinct is that some of the AI firms are overvalued and some of the companies that are beaten down are quite likely to be AI beneficiaries.

Still, I would not want to stake too much of my portfolio on that view.

Yet the high degree of concentration in today’s markets means that many investors are effectively doing so – which explains why they are prone to overreact in both directions.

Calm your AI boom worries

So how does you invest if you want to reduce these worries? Shortly before the market’s latest bout of nerves, I was at an event with Majedie Investments (LSE: MAJE), a flexible, long-term growth plus capital-preservation trust, whose approach offers some interesting ideas for this. Max King did a write-up on this trust a year ago, which you can read for more detail, but in essence Majedie holds a complementary mix of niche funds in specific areas (about 60% of the portfolio), direct investments in individual equities (about 20%) and special situations (the last 20%).

If you can find niches that have strong structural reasons for outperformance, or where an expert manager can consistently add value, you may be able to earn decent returns almost regardless of what is going in markets more broadly. You’re not going to be immune to the ups and downs, but the outlook for tech stocks shouldn’t dictate all the returns for activist Japanese small-cap stocks, biotech, distressed credit and so on. (Of course, identifying these niches and getting access to good funds is not easy, which is where Majedie’s managers need to do their job). Special situations should, almost by definition, offer very different returns to the wider market, while a global equity portfolio that is not benchmarked against the tech-heavy indices is also able to follow its own path.

Majedie’s strategy is distinctive in the sector and is performing well, making it worth a look in its own right, while the wider approach of putting together complementary strategies is a sensible solution, especially at times like this.

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The Chinese don’t seem keen on Sanae Takaichi, Japan’s new prime minister. According to Bloomberg, “thousands of Chinese travellers” are reconsidering trips to Japan in the wake of her comments that a crisis in the Taiwan Strait would be an issue for Japan’s own security.

They are in a minority. Across much of the rest of Asia there is a general view that a stronger Japan is a good thing for the region.

With the US a less certain ally than in the past and China increasingly aggressive – both economically and in the South China Sea – a Japan with firm opinions and defence spending at record levels no longer seems like a bad thing.

Domestically, too, Takaichi is exceptionally popular.

Her supermajority gives her, in theory at least, the ability to do pretty much anything she wants. That’s particularly the case given the breadth of her support.

There is an idea that her election is a function of an increasingly right-wing ageing population. Not so. She has strong support from the over-50s, but exit polls showed she is popular among the under-30s, too. She definitely has a mandate.

So what’s she going to do with it? Good things – if the money pouring into Tokyo’s stockmarket is anything to go by.

Long-term readers will know we have been bullish on Japan for well over a decade.

But pretty much everyone has now jumped on our bandwagon. Being all in on Japan is now a consensus.

The Nikkei is up 9% so far this year – and surged to a record high in the few days after Takaichi’s victory.

A large part of the excitement is about political stability. There aren’t many democracies at the moment where a leader can say they have been elected so firmly and with such a clear set of policies. It is also about those policies.

Japan’s long-term problem has been lack of investment. The low growth rate in Japan's economy over the last 20 years or so has been in part about a lack of investment – a decline in the capital stock.

This is why Takaichi’s budget for 2026 had spending rising by 6.2%, and a $135 billion stimulus package passed (and will now be enacted) in November last year.

That fiscal expansion is to be connected to an industrial policy that pushes capital towards AI, semiconductors, quantum computing, defence and shipbuilding.

Expect a clear tailwind for all these sectors – and some healthy growth and inflation ahead, even without China’s tourists.

Two not-so-nasty headwinds for Japan's economy

There are – or so we are told – two nasty headwinds for Japan's economy: its whopping public debt levels, and its falling population.

The first is probably overhyped.

Government debt is running at 230% of GDP. But it isn’t the whole story. Japan’s government sector as a whole owns financial assets worth a whopping 140% of GDP (net net, that already takes Japan to a lower ratio than the UK). And this doesn’t even include the Bank of Japan’s holdings, which are about half of all the Japanese government bonds (JGBs) in issuance.

It does include a lot of domestic equities and deposits, and foreign-exchange reserves held by the ministry of finance.

Do the maths, says Gavekal Research, and you will see that it is all kind of fine.

The government pays around 1.5% of GDP out in interest on outstanding debt – an effective interest rate of around 0.7%. If the US foreign-exchange reserves of about 30% of GDP earn the Federal Reserve rate of 3.5% and the rest gets the Bank of Japan policy rate (0.75%) it all adds up to around 2.5% of GDP.

Look at it like that and “there is ample fiscal room to absorb higher debt servicing costs from existing resources alone”. Maybe there is nothing for the bond market to see here (until interest rates rise too much – that’s another column).

The second headwind also isn’t the problem you might think it is. The Japanese population has been falling for years and the working-age population started to decline a few years ago. But it coincides neatly with the rise of the technology required to replace people – AI and automation.

There is a huge space for automation in Japan.

One minor example: even in central Tokyo not all convenience stores have self checkouts.

On a rather larger scale there is plenty of room for manufacturing to go “dark”: Fanuc already has a factory that can run full time for 30 days with no human supervision at all (these factories are known as “dark factories” because robots don’t need lights during the night shift). Expect more of these.

At the same time, as the votes for Takaichi showed, the young are happy with things as they are. They don’t remember the deflationary years so well and they live in a world where they should inherit a couple of houses, where their wages and disposable income are rising fast (one popular company in Tokyo just put up new graduate salaries by 30%) and where everyone is nice to them. Being a scarce resource isn’t all bad.

The sharp rise in Japanese stocks suggests that much of the good news is priced in. That said, with rising flows as investors rotate out of the US it is perfectly reasonable to expect tech, industrials and defence stocks to maintain momentum.

There is also an excellent chance that, with the indices at all-time highs and the optimism following the election, Japan’s institutional investors will finally move some money out of fixed income and into equities, says Chris Wood of Jefferies. When that happens, the market will “rerate in terms of multiple expansion”.

Merryn Somerset Webb hosts the Merryn Talks Money podcast for Bloomberg. Find her on X @MerrynSW

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Since at least the summer of last year, a large part of the financial commentariat has been waiting for the bubble in US AI stocks to burst.

Instead, something stranger is unfolding. In recent weeks, some leading technology names have suffered heavy sell-offs (Microsoft and Amazon are both off 17% since late January).

Yet AI continues to make progress.

Investors are beginning to seriously consider the implications of a world disrupted by the technology. Their conclusion? Today’s winners might become tomorrow’s laggards.

Software firms – first victims of the AI apocalypse

Those seeking to understand the success of US tech over the past 15 years need only consider the economics of software.

While developing a software product can be expensive, the marginal cost of shipping extra units is virtually zero. This makes software as a service (SaaS) ludicrously profitable.

Last year, Microsoft boasted gross margins of 68%. For comparison, supermarket Tesco’s gross margin is about 7%.

In 2011, venture capitalist Marc Andreessen declared that “software is eating the world”. Now AI is threatening to eat software.

On 5 February, start-up Anthropic launched the latest edition of its Claude Opus chatbot.

Highly capable at coding, it had been used to create a professional platform that performs basic legal analysis.

The implication is clear. If AI tools allow companies to create their own enterprise software in-house, why would they need to keep paying top dollar for a team of Silicon Valley software engineers to do it for them?

A major sell-off followed – dubbed the “Saaspocalypse”. The S&P North American Technology Software index has lost 30% of its value since the start of October.

Amplified by debt concerns, the world’s most profitable business model suddenly looks like one of the riskiest.

London’s small club of data-led firms wasn’t spared.

Everything from logistics to wealth management sold off as investors searched for new AI victims.

Yet despite the rout, the wider US market is flat for the year. Why? First, not all tech is in the doghouse.

Google is thought to have an AI edge because of all its data.

Hardware suppliers such as SanDisk and Western Digital remain in hot demand.

Second, some old-economy stocks are enjoying a lift.

Energy and commodity firms stand to gain from the data-centre build-out.

Industrials might be better positioned to pocket the gains of AI than the tech firms themselves.

Supported by the tailwind of an ageing population, healthcare is growing at a solid clip. If the rotation trend holds, then the FTSE, which is infamous for its “dinosaurs”, might just be set for a revival.

Yet uncertainty is rife. It will be a long time before we get a clear idea of the real winners and losers from AI disruption, says Jim Reid of Deutsche Bank. “That leaves plenty of room for investors’ imaginations… to run wild.”

Expect a volatile year with lots of “big sentiment swings” ahead. As for investors, remember that, “as with all disruption, opportunities will abound”.

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Global equity markets are increasingly fragile, dominated by the US, which in turn is heavily influenced by the AI boom. Many investors are therefore exposed to a single dominant theme. The vast sums being spent on building AI infrastructure support the US economy, driving the stock market and bolstering consumption through the wealth effect.

Global equities have become dominated by the US and by AI, leaving markets highly concentrated and expensive. Should this spending be questioned and ultimately reigned in – expected given uncertain returns on capital – the effect will be material.

Meanwhile, investors have sought to price the effects of AI on individual businesses. Broadly, hardware companies have been bid up as the clear beneficiaries (witness Nvidia), whereas many software firms have suffered owing to perceived risk of disruption.

AI is a transformative technology that will reshape economies, but we believe this effect will take years to develop, suggesting investors have overemphasised near-term effects. If enthusiasm for AI wanes and spending is curtailed, this “hardware good, software bad” dynamic may well reverse. In our view, this creates a great opportunity.

Beyond the AI boom: three low-risk stocks with long-term promise

Two companies that we consider fit the bill are ADP and Accenture. Automatic Data Processing (Nasdaq: ADP) is a high-quality, defensive compounder with a dominant position in global payroll and management software. It benefits from massive scale, deep regulatory expertise, and high switching costs, supporting recurring revenues and strong client retention. Structural tailwinds – outsourcing, workforce complexity, and cloud adoption – support steady mid-single-digit growth, making ADP attractive to long-term, low-risk investors. We think it may well benefit from AI being deployed, rather than suffering.

Accenture (NYSE: ACN) is a global leader in IT consulting and digital transformation. It benefits from long-term structural tailwinds, including cloud migration, data and AI adoption, cybersecurity, and initiatives to improve companies’ efficiency. A largely variable cost base supports margin flexibility through cycles, while strong free cash flow underpins consistent capital returns. Its execution track record and exposure to mission-critical spending make it a high-quality compounder over time. As AI becomes ubiquitous in the global economy, we expect it to bolster demand for Accenture’s services and improve margins.

A separate but attractive opportunity, unrelated to AI, is Novo Nordisk (Copenhagen: NOVO-B), a pioneer in anti-obesity medications. The stock has slid by 70% in 18 months, which we believe reflects overly pessimistic views on competitive and pricing pressures, rather than any permanent impairment of the franchise.

Novo remains the clear number two in a structurally attractive, underpenetrated global obesity market expected to burgeon over the next decade. Novo’s valuation has fallen to 13 times earnings at the lows – well below historical levels – despite exceptional returns on capital and strong cash generation.

New leadership, strategic pricing moves to expand access (notably with oral GLP-1s), and a credible next-generation pipeline led by CagriSema all bode well. Sentiment and expectations have overshot fundamentals, creating an attractive entry point with asymmetric upside as growth normalises from 2027 onwards.

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Andrew Van Sickle: A recurrent theme this year, and the subject of one of your key research papers, was drawing parallels between the dotcom bubble and this AI boom. What’s your take? Is this a case of rational exuberance?

Rob Arnott: It is a case of rational exuberance, with somewhat irrational pricing. To be clear, AI is the real deal. There is no ambiguity about that. It will change our world in more ways than we can imagine.

It was the same story in 2000. The internet was going to change everything: how we buy and sell goods and services; how we communicate with family and friends – or clients; how we get our news; how we do our research. And all of that happened. It’s just that the internet wasn’t embraced as rapidly as its cheerleaders expected, and I think the same will be true with AI.

A vital issue the narrative in 2000 missed was that the biggest stocks at that stage weren’t necessarily going to be the leaders in 2010, let alone 2020. I recall Cisco Systems’s chairman in 2000, John Chambers, saying he didn’t see why Cisco couldn’t grow sales by an annual 40% for years to come. At that pace you grow sixfold in five years. In fact, it grew sixfold in 25 years. Still impressive, but not 40%. As a result, investors holding Cisco since March 2000 are slightly in the red.

Of the top-ten companies by market capitalisation in 2000, only Microsoft remains on the list today. The other nine have all been displaced. Intel and Nokia were on the list, for instance. Other firms became better at producing chips and phones. People talk about companies having moats (competitive advantages that stop rivals from encroaching on their territory), but moats don’t last forever.

AI is already displacing current market leaders

There has already been some of this sort of displacement with AI. Google’s core business model is making money from sponsored links and pop-up advertisements. People discovered that ChatGPT or Perplexity can be used as a search engine, and you don’t get annoying pop-ups and sponsored websites; no need to scroll through a dozen sponsored websites to get to something useful. Moreover, OpenAI itself was disrupted a year ago by DeepSeek.

So this is a rational bubble in that AI is very real. All the market leaders have a shot at being dominant players for years. But I also recognise that some of them will be displaced.

Andrew Van Sickle: Could you give an example from your experience that makes you think AI is the real deal, as you say?

Rob Arnott: The latest iteration of ChatGPT is extremely impressive. When we write a research paper, we hand it over to AI and ask it to write a summary and critique it. We also get it to tell us if we’ve missed any references or citations that we ought to have considered.

We ran a paper we recently finished through ChatGPT and got an elegant synopsis that was better than anything the authors could have come up with. We also got a thorough evaluation of what was good about the paper and what wasn’t so good, along with a list of citations we’d missed. Four of them made us think: “Oh, my goodness, we should have thought of that one.” Four were borderline, and two didn’t exist.

The upshot is that AI can’t think like a person, but it’s excellent at scouring data and comparing it with information it has already absorbed. It can sift data sets of billions and billions of data points and then it will start to appear close to being human. If there are fewer data points, though, it will struggle badly.

For example, when it comes to researching long-term stock market behaviour there are only thousands or millions of data points, depending what we’re looking at, so AI can’t come close to the efficacy of human judgement supplemented by ordinary statistical tools. It can’t predict things like whether there will be a market downturn or recession. In short, AI is a quantity, not a quality game.

Andrew Van Sickle: Given the recent emphasis on technology growth stocks, where do you, as a value guru, see bargains?

Rob Arnott: The spread between growth and value is wide everywhere; globally speaking, it is near record territory. In the US, it is close to the level seen at the peak of the dotcom boom and the summer of 2020.

I would say don’t abandon growth, but don’t overweight it. Betting against a bubble is dangerous because bubbles can last longer and go further than you can imagine. So to the extent you have value in your portfolio, put more money into that.

We at Research Affiliates are always keen to find value and reduce concentration risk. We came up with the Research Affiliates Fundamental index (RAFI) series in 2005. These indexes are skewed towards value. The companies are weighted by their size and hence their economic importance – using measures such as sales, cash flow, book value and dividends – rather than share price. This approach has done much better than market-capitalisation-weighted value indexes, proving superior in three out of four years.

So investors might like to research the RAFI-based exchange-traded funds (ETFs) from Invesco that focus on value. There is the FTSE RAFI All World 3000 Ucits ETF (LSE: PSRW) for a global play; the FTSE RAFI US 1000 Ucits ETF (LSE: PRUS) for US value; and its European counterpart the FTSE RAFI Europe Ucits ETF (LSE: PSRE). The FTSE RAFI UK 100 Ucits ETF (LSE: PSRU) is a British version.

Andrew Van Sickle: Let’s move on to gold. It appears to be pausing for breath. Is the medium-term outlook still bullish, do you think?

Rob Arnott: The biggest factor that’s bullish for gold is the developed world’s addiction to debt-financed government spending. The fear is that fiat currencies will create their own financial crisis that could be bigger than the global financial crisis of 2009; I think that’s reasonably likely.

I don’t see it as an imminent threat. But just as Greece had to face the music at some point when its debt started to soar towards 200% of GDP, the US isn’t immune to that dynamic. We may be the biggest economy in the world, but that doesn’t mean we can endlessly spend money we don’t have. A crisis could arrive in ten to 15 years’ time.

It would require a severe bout of inflation to reduce the real value of the debt, and the consequence would be that the gold bugs of today would not regret their purchases even at today’s prices. That said, I am not a gold bull for 2026, given the recent surge to new records and the froth in the market.

Andrew Van Sickle: What could the result be of Donald Trump’s apparent desire to influence the level of interest rates set by the US Federal Reserve?

Rob Arnott: The upshot may be that he will keep rates 1% or 2% below where they ought to be, resulting in free money, which I define as rates below inflation: negative real rates. We had a dozen years of free money in the US, which was a key reason for slow growth.

The trouble is that stimulus doesn’t stimulate. My colleague Chris Brightman has written a great deal on stimulus failing to generate sustainable, healthy growth; you can find some of the papers on our website. Monetary stimulus leads to asset bubbles, exacerbating wealth inequality. It pushes money into the hands of people who are already well off, and they spend it, boosting corporate profits and stimulating the stock market further.

Part of the overall stimulus in recent years has been fiscal, too. That involves the government either taxing or borrowing money out of the private sector and then spending it, so it can hardly stimulate private enterprise.

Andrew Van Sickle: What is the outlook for US inflation? Will the tariffs boost it?

Rob Arnott: What could make inflation jump again is massive overspending, which we’re still doing, so that is a dangerous game. I wouldn’t view tariffs as particularly inflationary, however. I remember many analysts panicking early last year about a deep recession and hyperinflation.

But think it through. If the tariff rate settles at an average of 15%, it’s no different from a 15% VAT levy – applied in a limited way, solely to imports. That’s hardly catastrophically inflationary. It’s a tax. It boosts costs on taxed items. But if our imports in the US are worth 11% of GDP, and if we have an average tax of 15%, then it’s going to raise 1.6% of GDP in tax revenues. And that’s exactly what happened.

So who pays it? The suppliers swallow part of it to remain competitive in the US market; the supply chain takes some of the strain. The consumer has to pay the rest, perhaps half, or 0.8% of GDP – as a one-off. As a libertarian, I think the correct tariff rate is 0%. But the tariffs aren’t going to send inflation rocketing.

Trump’s tariffs games are essentially him implementing a strategy from Sun Tzu’s The Art of War: scare your adversaries and you can win without firing a shot. So, he threatens 100% tariffs and opts for far less. He’s lived by that book for his entire life.

Andrew Van Sickle: Last time we talked, you said you thought China had taken a statist turn under Xi Jinping. He has recently said he wants to make bolstering the private sector more of a priority. Has the regime realised that it will need to be more free-market to get China out of this debt deflation?

Rob Arnott: The trouble is that Xi Jinping is an unreconstructed Maoist, and so paying lip service to the private sector is about as far as he is likely to go. I still think China will get old before it gets rich.

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Emerging markets came into focus over the course of 2025 amid a volatile global backdrop. Heightened geopolitical tensions and uncertainty over US trade policy caused periodic bouts of weakness, as investors assessed the potential impact of tariffs on global trade and growth.

However, these concerns also contributed to a weakening of the US dollar, a dynamic that has tended to be supportive for emerging markets by easing financial pressures and allowing for more flexible policy. This trend was reinforced as some investors began to reassess the risks of over-concentration in US assets and diversified more actively into other markets.

In this environment, opportunities across emerging markets have remained uneven and recovery has played out differently by country and sector, with stronger momentum in parts of Europe, in technology-linked markets in Asia, and a more cautious – but improving – outlook in China. Against this backdrop, active stock selection is critical. The following three stocks reflect our approach to investment.

Focus on technology to profit from emerging markets

National Bank of Greece (Athens: NBG) reflects the ongoing repair of parts of Europe’s financial system. Greece has emerged as one of the clearer recovery stories, supported by improving macroeconomic fundamentals, resilient private consumption and a sustained reduction in public debt, culminating in a return to investment-grade status.

NBG has completed a long period of restructuring and now benefits from a large deposit base and strong capital ratios. The resumption of dividend payments after a 16-year hiatus reflects the strengthening of its balance sheet and operating position, as well as a more stable domestic backdrop.

Within the technology sector, Taiwan Semiconductor Manufacturing Company (Taipei: 2330) provides direct exposure to sustained investment in AI and cloud computing. Increased capital spending by global technology firms has driven demand for advanced semiconductors, where manufacturing capability and scale are critical. As the world’s leading producer of advanced chips, TSMC is a leading beneficiary of this demand. Its technology underpins applications ranging from AI to cloud infrastructure, and its position within global supply chains reinforces Taiwan’s importance as a semiconductor hub. This combination leaves TSMC well placed to benefit as investment in advanced computing capacity continues.

Tencent (Hong Kong: 700) operates one of China’s largest internet platforms, spanning online gaming, digital advertising and cloud services. Earnings growth has been driven by unexpectedly high revenues from gaming, AI-enabled improvements in advertising, and a recovery in the cloud business. The company has also sharpened its focus on capital discipline, reflected in an increased emphasis on dividends and returns for shareholders.

This progress comes despite a more mixed market backdrop in China. Targeted policy measures have recently helped stabilise sentiment, while innovation remains a defining feature of the technology sector. Developments such as the launch of the DeepSeek AI platform underline China’s continued role in AI, supporting longer-term demand for cloud, software and digital services – areas where Tencent remains well positioned.

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Matthew Partridge: Philippe Aghion, you won the Nobel Prize in Economics, along with Joel Mokyr and Peter Howitt, for explaining “how innovation provides the impetus for further progress”, especially through “creative destruction”. How does creative destruction spur economic growth?

Philippe Aghion: My view of creative destruction is that growth is created by the emergence of new talents and ideas, which challenge yesterday’s innovators and force them to keep innovating, or be pushed out of the market – with the newcomers eclipsing them.

So a dynamic economy is one where talents are always allowed to enter a market to grow and make money, but once they’ve grown up, they should not be allowed to use their rents to prevent newcomers establishing themselves. That’s where competition policy is so important. Otherwise, yesterday’s innovators will use their power to collude, preventing new innovations and the emergence of rivals.

Matthew Partridge: Over the past year, there has been a big move towards protectionism with Donald Trump’s tariffs, but also with the EU and its national champions. Do you see this as a threat to competition?

Philippe Aghion: Yes, competition is threatened on several levels. In the US itself, you see a collusion between vested interests and the governments, as epitomised by that photo of Elon Musk in the White House. Such “crony capitalism” inevitably leads to a situation where the incumbents collude with government to prevent new potential rivals entering the market, which is always bad news.

Similarly, trade barriers hamper innovation. Free trade gives you a bigger market for your innovations, which means bigger profits, as well as more pressure from competition. International trade also favours the transfer of technology from more to less developed countries, which is what allowed China to grow and India to escape poverty.

Matthew Partridge: Do you see the dominance of the “Magnificent Seven” as bad for competition, or an inevitable by-product of economic change?

Philippe Aghion: During the early stages of the IT revolution between 1995 and 2005, the big technology firms really boosted economic growth, as they knew better than other companies how to harness the power of IT. That is how you ended up with the likes of Google and Microsoft. Over time unrestricted mergers and acquisitions (M&A) and lax competition policy has squelched competition, restricting the entry of new companies. That is at least part of the reason why productivity growth has slowed down since 2005.

I’m worried we’ll see the same thing with AI, given Amazon and Microsoft’s dominance in cloud computing, a core part of AI. The sheer muscle of a handful of firms when it comes to chips could limit the adoption of AI. So, while AI has huge growth potential, we need a competition policy that either forces firms to share data, or breaks them up if they don’t. We must also block anti-competitive mergers.

Matthew Partridge: So essentially you’d like to see a more aggressive competition policy?

Philippe Aghion: Yes, although it’s a question of balance because over-regulation can harm competition too: incumbents always know how to deal with regulators better than new companies do. My advice is to extend the Digital Market Acts in Europe to the whole value chain of AI, including the cloud, and when you decide whether or not to allow a merger, don’t just look at market share, but also at the extent to which the tie-up might stifle future innovation and the emergence of new rivals.

Matthew Partridge: Creative destruction can be very positive for society. But by its very nature it involves losers. And sometimes, those losers are not only companies, but entire industries and the people who work in them. Is there a need to compensate the people thrown out of work, or revamp social safety nets?

Philippe Aghion: There will definitely be some job losses from AI, which makes it particularly important to have a good system in place to smooth things for the average citizen. I’m a particular fan of the Danish flexi-security system. There is a flexible labour market, but the unemployed get 90% of their salary for up to two years while the state retrains them. This makes creative destruction both more efficient and also much more friendly to the average citizen. However, remember that AI will create jobs as well as destroy them, not least because it makes it easier for people to come up with new ideas.

Matthew Partridge: Tell me more about your research on the impact of AI on productivity and employment.

Philippe Aghion: My feeling is that some jobs, particularly administrative and clerical jobs that involve many tasks that are highly substitutable by AI, might be at risk. However, there are two counteracting forces. Firstly, firms that adopt AI will become more productive and competitive, leading to increased demand for their products. AI is also an excellent tool for recombining old ideas to create new ideas, which in turn will create new tasks and new jobs. So, while there will be some job destruction, there is also scope for job creation.

This is why it is crucial is to have a good education system (as measured by the OECD’s Pisa assessment), which ensures that the average citizen knows how to master everything from basic skills, such as reading, through to more advanced concepts such as calculus. So the solution to job losses caused by AI is better education and flexi-security.

Matthew Partridge: In a recent paper, you and Simon Bunel came up with the estimate of AI boosting productivity by around 0.68% a year.

Philippe Aghion: If we just look at the number of tasks that AI automates, then the measured benefits are probably going to be around 0.68% a year, slightly less than the impact of the digital-technology wave of the late 1990s and early 2000s in the US, but roughly in the same ballpark. But this probably slightly underestimates the impact of AI because it omits the extra growth gains from the fact that AI can help generate new ideas and technologies. Of course, if we don’t adapt our competition policy, and the incumbents manage to squelch innovation, then the boost might be much smaller. Like my co-laureate Joel Mokyr, I am rather optimistic about technology, but only moderately optimistic about the speed of institutional change.

Matthew Partridge: You’ve talked about the importance of intellectual property (IP) rights for encouraging innovation. Given that a lot of AI consists of copying or adapting people’s work, does there need to be some sort of change to simply prevent AI becoming a tool of mass piracy?

Philippe Aghion: I definitely don’t believe in a complete free-for-all. We need at least some regulation to secure IP rights, otherwise we discourage innovation altogether. But the thing is not to over-regulate and thus discourage new entrants. We need the right balance.

MP: You’ve also done research on the middle-income trap: the fact that some countries seem to reach a certain level of development and then just get stuck there. Could you tell us about that?

Philippe Aghion: A good way to understand the middle-income trap is to take South Korea. After the Korean War, it left North Korea in the dust, growing at a high rate thanks to a successful education system, which produced a workforce with a high level of scientific knowledge that allowed it to imitate more advanced technologies. The problem, however, is that at some point you exhaust the power of imitation and need to start moving into innovation-based growth, or “frontier innovation”, as I call it.

However, frontier innovation requires competition, and during the catch-up phase South Korea developed large firms called chaebols. They discouraged the entry into the market of non-chaebol firms and put pressure on the government not to move towards institutions that would favour frontier innovation, as that would threaten their monopoly, which has slowed down South Korea’s overall economic growth.

Even Japan, a much more successful nation, has had a similar problem with the keiretsu, companies whose post-war dominance has prevented the government from adopting more pro-competition policies.

Matthew Partridge: What about Europe?

Philippe Aghion: Europe suffers from some of the same problems as South Korea. It did a very good job of catching up with the US between 1945 and 1995, but since then, the gap in per-capita GDP has started to widen again. This is because, as Mario Draghi’s report The future of European competitiveness – A competitiveness strategy for Europe notes, the single market in goods and services hasn’t really been completed, so there isn’t enough competition between firms. Many companies are therefore still making incremental improvements rather than engaging in disruptive innovation.

Europe also doesn’t have a proper financial “ecosystem” for frontier innovation, especially in terms of venture capital. Institutional investment into start-ups is underdeveloped in Europe compared with the US. And while Europe funds some research into science through the European Research Council, we don’t have enough money for long-term research that might only pay off ten years down the line. We need an equivalent of America’s Defence Advanced Project Agency (DARPA), a pro-competition way to do industrial policy.

Matthew Partridge: How should the UK boost its poor productivity?

Philippe Aghion: I think it has definitely suffered from Brexit, especially given the negative effect that leaving the single market has had on competition and reducing the total size of the market. My hope is that the UK now wants to collaborate a lot more with European countries, which can only be good for both sides. I’m very much in favour of the EU working with the UK on defence, on health, and in energy. Where the EU and UK can implement the Draghi report together, they should.

Philippe Aghion is chair of Economics of Institutions, Innovation and Growth at the Collège de France and the Kurt Björklund chaired professor in Innovation and Growth at INSEAD. He is also a visiting professor at the London School of Economics.

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I never take the flood of forecasts that investment banks and brokers produce at the start of the year very seriously, but this isn’t because the analysts who produce them are fools. Most people who work in these jobs are smart and knowledgeable. Yet the tendency of the investment industry to reward moderate bullishness at all times means that very few can put out a genuinely unconstrained view.

There are not many analysts who have the freedom to write that they think investors should have zero exposure to the US, as Jeremy Grantham argues. Right or wrong, it is clearly a strong opinion, while simply saying that investors should be “market weight” in US equities does not offer much to chew over.

Still, when you read enough of these reports, you at least get a clear sense of whether the consensus lies. While this is far from scientific, a quick overview of the thinking for 2026 probably runs something like the following.

AI spending is forecast to rise in 2026 – should investors keep backing it?

Spending on AI will keep rising, but the prospects for a technological revolution are so great that the bigger risk is not being invested. (It’s notable that fund managers seem to be rather more worried about whether there is an AI bubble than brokers are.) Stocks will go up, although there is much less optimism than last year about whether America will outperform the rest of the world after it fell behind in 2025. No region seems to stand out as a consensus pick, although there is quite a bit of interest in Japan. Interest rates will fall, especially in the US, which will be good for bond markets. However, nobody is getting especially excited about traditional credit (eg, corporate bonds) – not because they are forecasting disaster, but because valuations are fairly steep: there’s not much extra yield to pick up from riskier bonds compared to safer ones. Conversely, enthusiasm about private credit (eg, loans made directly by investors to companies) still seems high, despite a couple of high-profile defaults in the past year. Oil will remain under pressure. Gold will keep going up. Industrial metals such as copper and aluminium could do well due to tight supply and rising demand from AI infrastructure.

The biggest shift compared with last year seems to lie in the currency markets. Back then, the consensus was that the dollar would keep getting stronger as a result of foreign capital flowing into US markets and Donald Trump’s policies being helpful for the US trade deficit. In the end, the dollar weakened against most major currencies in the first half of the year before stabilising.

This year, most forecasters expect a weaker dollar, on the basis that interest rates will fall faster in the US than elsewhere. The other reason to expect this largely goes unsaid: the tail risks created by the Trump administration’s increasingly unpredictable policies are changing how investors feel about the US and making them – at the margin – more inclined to look for opportunities elsewhere. Based on the events of this week, we should expect that to continue.

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The leisure sector is but part of the gigantic services sector, which accounts for roughly 80% of UK GDP. The latter encompasses everything from professional services such as solicitors and accountants, to restaurants and coffee shops, banks and everything in between. As a result, the entire sector is connected to the consumer in one way or another. Whether it’s the waiter in the restaurant, or the highly-paid accountant that works for a US investment bank who buys a £15 lunch every day, the services sector, the consumer and leisure spending all go hand in hand. To put a number on it, consumer spending accounts for about 60% of UK national output, with the bulk of this generally described as non-discretionary spending on items such as food and drink.

Around 10% of the UK’s workforce is employed in what you could call the “discretionary” leisure sector, which encompasses businesses such as pubs and restaurants, hotels, travel-related firms, gyms and other similar businesses. A large segment is the travel sector, which, according to government figures, is worth around £70 billion a year, split roughly in half between domestic travellers and international visitors.

Challenging years for the UK leisure sector

The past year and a half has been a tough time for the UK leisure sector. It is highly dependent on the health of the consumer, both financially and in terms of confidence. Most data and surveys show they are becoming more cautious with their money, so they’re prioritising non-discretionary spending. Consumer spending tends to rise when consumers perceive their discretionary income to be increasing. When consumers perceive that to be declining, they stop spending, and that’s bad news for the leisure sector.

The latest data from Barclays on consumer card spending shows that it fell 1.1% year on year in November – the largest fall since February 2021. A survey from the British Retail Consortium trade body showed spending at big retailers rose by 1.4% in annual terms in November, the slowest growth since May. Consumer spending on leisure was relatively stable in the run-up to the pandemic, before dropping off a cliff in the first quarter of 2020, according to Deloitte. Sentiment and spending bounced back in 2021, but since May 2020, consumers have remained cautious due to rising prices, stagnant wages and political uncertainty. Analysts expect this trend to continue. According to the Office for Budget Responsibility and the Institute for Fiscal Studies, consumer discretionary income is expected to rise by just £100 a year, or thereabouts, until the end of the decade.

As spending has stagnated, costs have continued to rise. Energy, tax and wage costs have all risen substantially over the past three years, and it doesn’t look as if that is going to come to an end any time soon. In the Autumn Budget, the chancellor announced the national living wage would rise by 4.1% in April to £12.70 per hour, while the hourly national minimum wage would rise by 8.5% to £10.85. This followed a near 10% increase in the national living wage for workers over the age of 21 in 2024, which, when combined with the increase in employers’ national insurance, sent the cost of labour skyrocketing in the labour-intensive service sector.

Changes to business rates announced in the Autumn Budget are also going to increase the tax burden on businesses next year. The government claims it is keeping the increases down for the hospitality sector by phasing in the changes over three years, but the UK Hospitality trade body estimates that an average pub will pay £12,900 more over the next three years, while an average hotel will pay £205,200 more. Days after the Budget, Whitbread, the owner of the Premier Inn chain, said the changes would push costs higher across the business by 7% to 8%, giving investors some idea of what’s in store for the sector next year.

With these headwinds buffeting the sector, it’s no surprise that equities in the sector have fallen by an average of 1.6% year to date compared with a 7.6% return for the FTSE All-Share index. However, despite the doom and gloom, on an underlying basis, companies seem to be managing. Trading has held up and margins have improved thanks to operational efficiencies and the implementation of new technologies. As a result, the sector is cheaper than it was at the beginning of the year, trading at an enterprise value to Ebitda ratio of 6.4 times, compared with 7.4 times at the start of the year, and a p/e ratio of 11.8 times compared with 13.5 times, according to Panmure Liberum. There’s also growing evidence that consumers are in a far better position to spend as we head into the new year.

Consumers seem to be spending regardless

The average UK consumer, while not spending as much as the leisure sector would like, has a strong balance sheet. The percentage of disposable income that’s not spent on consumption (ie, is saved) rose to 10.7% in the second quarter, above the three-year pre-pandemic average of 5.6%, according to the Office for National Statistics. So consumers have money to spend if they want to spend it. There’s also been a shift in how consumers want to spend their money over the past three years, as the world has bounced back from Covid.

Consumers want to spend money on experiences, and are more than happy to pay for a one-off, unique experience that they can’t replicate. They also appear to be more willing to spend on big-ticket events and experiences. According to the YouGov GB Dining Out Report in October, 38% are eating out less than they did a year ago. Even for higher-income diners, that number is 29%. But a recent report by Bloomberg cited examples such as Hawksmoor and Gordon Ramsay restaurants, as well as high-end Michelin-star restaurants, that are recording bookings far in excess of last year’s figures, in some cases by as much as 30%.

And reading through the recent trading statements of companies in the sector, it’s clear consumers are spending more when they do put their hands in their pockets. Mitchells & Butlers (LSE: MAB), JD Wetherspoon (LSE: JDW), Fuller’s (LSE: FSTA) and Young’s (LSE: YNGA) have reported like-for-like sales growth of 3.8%, 3.7%, 4.6%, and 4.2% respectively in the run-up to Christmas – all ahead of the market. Young’s and Fuller’s are particularly notable, as they are more of a premium offering than the rest of the market.

Then there’s the data from travel company On the Beach (LSE: OTB). Alongside its results for the year to the end of September 2025, it said it expected a record summer in 2026, with 8% year-on-year growth, following 11% growth in 2025. Winter 2025 forward bookings were up 15%, it said, with four- and five-star holidays now accounting for 80% of the total. EasyJet (LSE: EZJ) has reported that 80% of its bookings are sold for 2026, with prices up by double-digits. It expects a 15% rise in customer numbers in 2026.

Everyman Media Group (LSE: EMAN), the operator of luxury cinemas, has said that while the UK box office has been “weaker than expected” in the fourth quarter, it has seen increased spending per head among customers visiting its venues. For the 26 weeks ended 3 July 2025, ticket prices and food and drink spending per head rose around 6% year on year.

Next (LSE: NXT), often considered the bellwether of the UK retail sector, has smashed its own expectations for growth this year. Over the 13 weeks to 25 October, full-price sales were up 10.5%, ahead of guidance of 4.5%. International growth helped, but full-price sales in UK stores rose by 4.3% and online sales by 8.7%. There’s even data showing that consumers are willing to pay more for everyday essentials. According to Which magazine, Ocado (LSE: OCDO), one of the most expensive supermarkets, ended its half-year to the beginning of June as the UK’s fastest-growing grocer over the previous 12 consecutive months. Revenue rose 16.3%, ahead of the market, as order volume per week jumped 14.7% and the average value of a basket of goods grew by 0.7% to £124.19.

Investors cannot ignore the cold, hard sales figures on the ground. All of these companies are recording robust growth that runs counter to the overarching narrative presented by surveys and the media. This suggests that some of the doom and gloom on the UK leisure sector is sentiment- and confidence-driven rather than an accurate reflection of spending patterns. Now could be the time for investors to leap in.

Leisure stocks are going cheap

The good news for investors is that some of the most attractive leisure stocks are currently trading at deeply discounted multiples, most likely a reflection of the poor sentiment towards the sector and consumer spending. This means there’s already a strong margin of safety baked into the names, limiting the downside if the environment is worse than trading updates suggest.

Marston’s (LSE: MARS) is one company that stands out in particular. Trading on a forward p/e multiple of seven for 2025, falling to 6.4 for 2026, you would think the company is struggling, both in terms of growth and financial sustainability. However, it recorded a 71.3% increase in profit before tax in its latest preliminary results. Sales increased 1.6% on a like-for-like basis, and its Ebitda margin expanded 140 basis points. Over the past two years, the company has seen a substantial decrease in net debt and interest costs as a result, with borrowing now down at 4.6 times Ebitda compared with management’s target of four. Free cash flow is in the region of £50 million, putting shareholder returns firmly on the radar for the first time in recent memory. The pubs and bars group is expected to report its Christmas trading in January 2026, but it has already said that Christmas bookings were up 11% on last year’s levels at the end of November. This is one stock that could see a substantial re-rating if the market comes to appreciate its turnaround story, valuation and growth potential.

Profiting from salad

Self-help initiatives always help unlock value for shareholders and catalyse a re-rating of undervalued equities. SSP Group (LSE: SSPG) sits on the edge of the UK leisure sector with a large international business, but is worth considering, with multiple levers to unlock value. The group, which owns brands such as Upper Crust and franchises including M&S and Burger King, runs concessions mainly at travel hubs worldwide – it’s the world’s second-largest operator in the space. SSP’s latest trading update recorded revenue growth of 6%, with especially strong performance in North America and weakness in continental Europe. Management has commissioned several strategic reviews of the portfolio recently, including a review of its Continental European Rail, a perennial underperformer. The group also holds a 50.1% stake in an Indian joint venture, Travel Food Services.

The latter listed in India last year and is trading at a higher valuation than its parent company K Hospitality. With Indian listing rules requiring a 25% free float in three years from listing (it listed with a 13.8% free float), SSP could sell some of its stake over the coming years, unlocking cash for investors. The sale of the firm’s underperforming businesses, as well as unlocking cash from Travel Food, are both potential catalysts for the stock, currently trading at a forward p/e of just 12.4. That’s also relatively cheap for a company that generates a pre-tax return on capital employed – a measure of profit for every £1 invested in the business – of 18.7%.

At the smaller end of the spectrum, Tortilla Mexican Grill (LSE: MEX) is worth a look. The company has a market capitalisation of just £16 million, so it’s probably not suitable for every investor, but it’s the fastest-growing business in the UK casual dining and leisure sector. The company recorded like-for-like sales growth of 7% in its latest trading update, more than double the market average, and it’s moving rapidly towards sustainable profitability as its store roll-out continues. The company, which creates “freshly made, award-winning California-style Mexican burritos and tacos”, has been leaning into the demand from UK consumers for healthy fast food. It launched a new menu, including items such as salad and protein pots, over the summer, and demand has been brisk, with salad volumes up 133% and protein-pot sales hitting £100,000 in the first eight weeks. Other new menu items are planned, as well as expansion into new markets. It’s rolling out new kiosks and has launched a franchising initiative with SSP.

However, it is struggling to digest its French business, Fresh Burritos, acquired in July 2024 for €3.9 million. An overhaul of the acquired brands is running behind schedule, and costs are growing, but it has given Tortilla a platform for growth within Europe. As these costs tail off, Panmure Liberum expects the business to earn its first profit of £1.6 million next year, rising to £4 million in 2027 as store openings continue. That would put the shares on a forward p/e of just five, dirt cheap for a company earning a return on capital employed (Roce) of 24% on its established UK arm.

On the Beach (LSE: OTB) is another operator with plenty of levers to pull to drive growth. As noted, holiday bookings are tracking much higher year-on-year, with consumers increasingly prepared to spend more. The company is also launching into new markets such as the Republic of Ireland, together with city breaks and cruises, to help complement its core beach-holiday arm (92% of business currently). The new city-breaks arm contributed 2% of the overall group’s 11% increase in total transaction value in fiscal 2025, highlighting the demand in this market. On the Beach’s cruise business is too new to judge at this stage, but this is a tried-and-tested market where the firm should be able to leverage its existing brand recognition to win further wallet share with existing customers. Analysts at Berenberg expect the company’s sales to rise 14% in 2026 and then 16% in 2027, driven by these initiatives and increasing customer spending. At the same time, they’ve pencilled in Ebit margin expansion from 24.7% in 2025 to 27.7%. Put all of the above together and the bank has pencilled in a p/e of 10.1 for fiscal 2026 and 8.1 for fiscal 2027.

Leveraging AI

Hostelworld Group (LSE: HSW) is a tech company masquerading as a leisure stock and is the world’s leading hostel-focused online booking platform. After building a solid growth platform over the past five years, the company is now midway through a plan to boost its exposure to customers earlier in the planning phase of their trips, leaning into the growing demand for experiences when travelling.

To that end, it recently acquired OccasionGenius, a US-based business-to-business event discovery platform. The platform leverages AI and technology, augmented with a human oversight layer, to aggregate resources, including national ticketing sites such as Eventbrite, Ticketmaster and thousands of “micro” sources, including local calendar sites and social media, to create marketing-ready content for its customers (such as hotels, dating apps and airlines).

Hostelworld has laid out plans to double OccasionGenius’s exposure, although it’s not expected to contribute meaningfully to the group’s bottom line in the near term. Expansion, plus increased booking demand, is expected to send sales up from £95 million to £118 million by 2027 and Ebit from £15.3 million to £22.5 million. However, what’s really notable is the group’s cash generation. The group is expected to move from a net debt to a net cash position of £21.4 million by 2027, compared with its current market value of £155 million. As such, on a net cash basis, the stock is trading at a sub-ten forward p/e ratio.

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Zohran Mamdani: A socialist takes New York

“We cannot have a socialist” running “the greatest capitalist city in the world”, observed one Wall Street financier just before November’s mayoral election. Get used to it, said The New Yorker. On New Year’s Day, Zohran Mamdani will become the first avowedly socialist mayor of New York, and its first Muslim leader to boot, following a meteoric rise. A year ago, most had never heard of the youthful Assembly member from Queens. But Mamdani’s rising star – on a platform of soaking the rich to fund rent freezes, free bus travel and universal child care – has proved unstoppable.

Donald Trump, who once called Mamdani a “100% Communist lunatic” and threatened to deport him, changed his tune when he met him, staging a surreally chummy press conference with his charismatic fellow populist. “As well as coming from nowhere” to win New York, Mamdani has “succeeded in setting” America’s domestic economic agenda in 2025, making the issue of “affordability” the watchword of his slick TikTok campaign. Born in Uganda, Mamdani, 34, arrived in New York aged seven. His unremarkable CV since might suggest he’ll struggle to run a city with “the economy of a medium-sized nation”, says The Economist. And his hands are tied: the state legislature seems unlikely to pass his full $9 billion package of tax hikes. But the city’s fate ultimately depends on whether Mamdani shows “a pragmatic streak”, says The Wall Street Journal – or views “his mission” as “creating a socialist lab experiment”.

Javier Milei: El Loco stands at a crossroads

Argentina’s chainsaw-waving “libertarian firebrand” Javier Milei narrowly escaped financial meltdown this year – helped by a $20 billion lifeline from the Trump administration to avert a currency crisis and “Make Argentina Great Again” – before pulling off a surprising landslide in the country’s midterm elections, says Bloomberg.

Nicknamed “El Loco” (The Madman) as a teenage goalkeeper, Milei has often seemed determined “to perpetuate this reputation with his egotistical boasts and brutal attacks on critics”, notes The Washington Post – not to mention “his crazy hair, cloned dogs and claims of expertise at tantric sex”. Yet since coming to power in 2023, the results of his far-reaching free-market reforms have been impressive, says The Economist. Inflation is down from 211% to around 30%, the poverty rate has fallen and “the budget has been wrestled under control”. Milei is now moving towards a floating peso and removing most capital controls. The process has been painful, but voters have kept faith with his vow “to jolt” Argentina “out of more than a century of statism and stagnation”. Markets, in turn, have celebrated, judging the prospect of Milei’s re-election next year now more likely. “Rev up the chainsaw!”

Much could yet go wrong. Milei is now at a crossroads, Carlos Malamud, a Latin America specialist at Madrid’s Real Instituto Elcano, told the Financial Times. “He has everything he needs, if he gets it right… to lead a deep transformation of Argentina.” But if “arrogance gets the better of him again”, all bets are off.

Sanae Takaichi: Japan’s Iron Lady

The new Japanese premier, who made history in October when she became the country’s first female PM, has proved a gift for headline writers. Known for her love of hard rock and motorbikes – and citing Margaret Thatcher as an inspiration – Sanae Takaichi has gone “from Iron Maiden to the Iron Lady”, says Sky News. But she has taken a battering at the hands of bond markets. Since taking power, and shocking investors with a “low quality” fiscal expansion of $135 billion – “including such gems as rice vouchers and subsidies for fossil fuels” – yields on Japanese debt have “spiked wildly across the maturity curve”, says The Telegraph. The risk that this could escalate into a major crisis in Japan’s historically sedate $12 trillion bond market “has sent tremors” through the markets.

When it comes to dealing with Donald Trump, she appears to have learned from her mentor, the late Shinzo Abe, that “flattery, deference” and golf-related “gold-plated gifts” were the way to go. “Takaichi’s smorgasbord of giveaways” may make a “mockery of Thatcherism”, but she does share some traits with her heroine. “Like the late Iron Lady, she has little patience for other career women,” says The Telegraph. She belongs to Nippon Kaigi, “a nationalist nostalgia movement that fights feminism and harks back to the Samurai ideal of women as the anchor of home and family”. Still, unless she is careful with bond-market vigilantes, Takaichi runs the risk of comparison with another UK Conservative prime minister – Liz Truss.

Liang Wenfeng: The hedgie who shook the world

The entrepreneur behind DeepSeek began 2025 with a shot that rang around the world, says Fortune. Billions of dollars were wiped off the value of Silicon Valley’s AI titans in January when the unknown Chinese start-up revealed its prowess at developing cutting-edge AI at a fraction of the cost – raising doubts, that have lingered all year, about the gargantuan sums being spent in the West. “Whether by chance or design”, the launch of DeepSeek’s R1 coincided with Donald Trump’s inauguration, says Time, creating “a powerful narrative” that China had “matched America’s best with just a fraction of the computing power”. It was hardly the best start in Washington to a year of tight trade negotiations.

Liang Wenfeng, 40, who hails from a village in southern China, isn’t a computer whizz so much as a financier. After graduating from Zhejiang University, he co-founded the quantitative hedge fund High-Flyer in 2016 – originally using AI as a trading strategy to predict market trends and help make investment decisions. In 2021, says the Financial Times, Liang began buying thousands of Nvidia chips as “an AI side project”. At the time, local business partners viewed this as “a quirky hobby”. But when he started DeepSeek in 2023 – and began challenging local rivals ByteDance and Alibaba – they sat up. DeepSeek has spent its short corporate life having to work around successive US bans on the export of vital chips to China. The upshot, says the South China Morning Post, is that Liang has become one of the most forceful drivers of China’s push for technological self-sufficiency.

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This year’s best-performing emerging market (EM) shouldn’t really be classified as an emerging market at all. South Korea’s high-tech industrial base is a match for any of the world’s leading developed economies. Yet restrictive trading rules on the local bourse see it consigned to the same global investing basket as Egypt and Peru.

Nonetheless, the local Kospi index has rocketed 66% this year. That reflects two massive tailwinds: AI, and a closing Korea discount. For the first theme, memory-chip champions Samsung and SK Hynix are cashing in on Big Tech’s splurge on semiconductors. For the second, Seoul has begun to implement pro-shareholder reforms, a copy of similar changes in Japan that unleashed a multi-year stockmarket rally.

Emerging market winners

Korea’s gains have helped push the MSCI EM benchmark to a 26% gain for the year to date. After years of lagging the developed-markets index, that rise comfortably outstrips the 18% gain for MSCI’s equivalent index for developed markets.

Those gains partly reflect more benign financial conditions for the developing world. US interest-rate cuts and a weaker dollar tend to push capital out of Wall Street and into more exotic locales. Yet the upswing has not been universal. This year’s big winners have tended to offer exposure to one of 2025’s two winning trends – AI-focused tech and the global metals rally. Like Korea, Taiwan’s Taiex (+20.5%) is rallying on soaring demand for AI equipment, largely driven by the enormous success of local chipmaker TSMC.

The mainland Chinese CSI 300 is up a healthy 17.5%; Hong Kong’s tech-biased Hang Seng has done even better, with a 28.5% gain. The east Asian economies now jointly account for 60% of the MSCI EM index, making the index a more concentrated bet than many EM investors would ideally like.

India, the index’s third-largest component, provides some diversification. The country’s thrilling growth story resembles that of China in the early 2000s. Yet share prices have become stretched, and the BSE Sensex’s 8% gain for the year is lacklustre. While India is a global leader in IT outsourcing, local markets offer little exposure to AI.

Southeast Asia is a mixed bag. Vietnam’s VN index has rocketed a third in the same year that it won an upgrade to emerging-market status by index provider FTSE Russell. Indonesia’ IDX Composite has gained 21%.

Malaysia’s KLCI is flat, while the Philippines’ PSEi index has slipped 7% amid signs of a domestic slowdown. Thailand’s SET index has retreated 10% as investors flee political turmoil and signs of a decline in the country’s crucial tourism sector.

Metals rally helps emerging markets shine

Gold’s 60% rally this year has helped South Africa to shine. The JSE Top40 index has had a banner year, with local miners and an improved political outlook propelling it to a 40% gain. Copper champion Chile has done even better, with the IPSA index enjoying a massive 50% rally.

But not all commodities are created equal. The oil-heavy Saudi Tadawul all-share is off 13% amid weak energy prices. The US has picked fights with both the Mexican and Brazilian governments this year, but you couldn’t tell by looking at their stock exchanges, up 28% and 32% respectively.

The White House’s 50% tariffs on Brazilian imports have “backfired”, because “Brazil exports more than twice as much to China as to the US”, says Craig Mellow in Barron’s. Brazil’s strength in agriculture makes it a highly complementary trading partner. Investors also hope that next year’s presidential election could bring a pro-market candidate to power, echoing Javier Milei’s success in Argentina.

It has been another good year for emerging Europe. Poland, the region’s biggest market, is catching up fast with western Europe. A boom in defence spending has helped push the WIG20 to a 39% gain. Finally, difficult post-crisis reforms continue to pay dividends in Athens. The ASE index has rallied 41% this year and 119% over the past three years. The protracted Greek tragedy is finally over.

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Our approach is to focus on quality companies, defined as those that have achieved a return on capital persistently above the cost of capital over time. These companies often pay a dividend as a result of the profitability they have generated in cash terms. Seen this way, the dividend is very much an outcome: a marker of the company’s economic productivity, and therefore, we believe, more likely to be sustainable and capable of growing over time.

This approach is distinctive in emerging markets, where it steers us away from the commodities roller-coaster and the cyclical sectors that accompany it, and towards companies with the more consistent, stable financial characteristics that we seek.

Three emerging market stocks to consider

Elite Material (Taipei: 2383) is one of the companies we own with exposure to hardware used in the AI-supply chain. The company is the leading producer of halogen-free copper clad laminate materials used in printed circuit boards, which have applications in IT infrastructure and cloud computing, but also in consumer electronics.

A key attraction of this long-held position is the company's ability to adapt to the changing demand cycle we have seen in information technology over the past five years. Thanks to a dominant position in a product that can be used in numerous applications, the company has been able to benefit from these varying peaks in demand and the current boom in spending on AI servers. Reflecting the recent enthusiasm in the market for AI stocks, the share price has more than doubled over the year to date. The company trades on just over 23 times forecast 2026 earnings.

Yili (Shanghai:600887), China's largest dairy company, produces fresh and Ultra High Temperature milk (representing around two-thirds of revenue), milk powder, and dairy products including yoghurt and cheese. China’s dairy market has been structurally challenged in recent years, but there are early signs that the supply-demand balance is starting to improve, which should ultimately lead to a recovery in milk prices.

Dairy consumption is at relatively low levels, particularly in comparison to developed markets, and we expect this to increase over time as consumer spending rises. At the same time, the company’s leading position across multiple categories and price points gives it a degree of pricing power. These two factors are the twin forces that should provide a strong tailwind. Scale also brings considerable distribution advantages. The company trades on 16 times forecast earnings and the trailing dividend yield is 4.5%. Earnings are expected to grow 10% next year.

Hypera (São Paulo: HYPE3) is a Brazilian consumer-pharmaceuticals group that has acquired a portfolio of market-leading brands in diverse categories such as pain relief, flu remedies and digestive health. The product line also includes dermatology and vitamin supplements.

The company has recently undertaken a programme to reduce excess working capital, a process now largely complete. Although the business is somewhat seasonal owing to the prevalence of cold and flu medicines in the company’s product range, we believe the valuation of the company to be very reasonable given the underlying quality on offer. The stock trades on 14 times forecast earnings and yields 4.7% on a trailing basis.

Three years ago, OpenAI launched ChatGPT, sparking a surge of interest in AI and sending the stocks of many of the world’s largest technology companies soaring. However, in addition to the likes of Microsoft and Nvidia, shares in many smaller companies have also rocketed thanks to their role in building the infrastructure required for the adoption of AI. However, investors are starting to wonder whether all this investment in the new technology is likely to prove profitable.

Their doubts are having a knock-on effect on some of the more contentious AI-infrastructure plays, such as Coreweave (Nasdaq: CRWV). Coreweave makes its money from building data centres full of high-end computer hardware that provide the vast amount of computing power needed to train firms’ AI models; it leases the data centres to companies willing to pay for them. So far, this seems to have worked well, with explosive demand causing sales to rocket from $15.8 million in 2022 to an estimated $5.1 billion this year, a figure expected to more than double again to $11.9 billion by the end of 2026.

Coreweave's business model is unsustainable

However, if you look more closely, it becomes clear that the business model is unsustainable. Running data centres is a business that rewards scale, says Sahm Adrangi of Kerrisdale Capital, which is why it is dominated by large cloud-computing providers such as Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle.

Coreweave’s relatively small size means that to compete with these players, it has had to offer large discounts and slash profit margins. What’s more, renting computer power can be a risky business because Moore’s Law means that most computer hardware becomes obsolete within a few years.

Andrangi argues that even in the best-case scenario, where demand for computing power continues to expand, Coreweave will struggle to make enough money to recoup the upfront costs of building the data centres, let alone make a decent return on investors’ money. If demand falters, the hardware becomes obsolete more quickly than planned, or firms start building their own data centres, then Coreweave could be in serious trouble, especially as it has taken on huge debts to finance its investment. Other red flags include the fact that the key insiders have started selling their shares in the company.

With Coreweave currently valued at around 10 times current sales, investors’ expectations for its future success are extremely high. And the market has been starting to get cold feet recently, with the stock falling by nearly a quarter in the last month alone. It is now down more than 50% from its highs this summer. This suggests that it is a good time to go short at the current price of $88, at £22 per $1. Given tech shares’ volatility, I suggest you cover your position if the price hits $132, which gives you a total possible downside of £968.

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Private credit is not the catchiest topic. Put it alongside AI or bitcoin, and you can see why it doesn’t make so many headlines. Yet there has been a growing stream of stories over the past year or so about the potential risks that could be lurking in the sector, to the point where big names such as Marc Rowan of Apollo apparently feel the need to step up and defend it.

Shares in Blue Owl Capital, which is exposed to some of the main worries that investors have about private credit, have fallen about 30% this year. It has done noticeably worse than private-markets peers such as Apollo or Ares, which are big players in private credit, but have a smaller proportion of their overall business there.

These jitters may be pretty much irrelevant unless you are investing in private credit. I am a little sceptical about it as an investment, but that doesn’t mean that losses will have much impact on other markets. If private credit has indeed taken lending off bank balance sheets – as supporters claim – it could even reduce the consequences of higher defaults.

Private credit's link to the AI boom

Still, investors who remember the global financial crisis will recall the structured finance boom – mortgage-backed securities (MBSs), collateralised debt obligations (CDOs) and an alphabet soup of other vehicles. These were also supposed to redistribute risks and make the system safer. They ended up doing the opposite. That does not mean that private credit is likely to do the same – there are very significant differences between direct lending and structured finance. It only means that investors should be alert to unexpected consequences.

One of the intriguing aspects of private credit is the growing link to the AI boom. Data centres cost a great deal of money and private credit seems to be funding more of it: UBS estimated in August that private credit to the tech sector had risen by $100 billion (or 29%) in 12 months.

For example, Meta Platforms is building a $27 billion data centre in Louisiana, financed by Blue Owl’s funds. The accounting in this deal is intriguing: the liability is mostly off Meta’s balance sheet on the basis that the tech giant only enters into a four-year contract, renewable every four years – even though it provides a “residual value guarantee” to protect bondholders if it doesn’t renew. Still, Meta is probably good for the money. Some of the other data-centre firms will not be if their customers walk away.

Does this mean that an AI bust would ripple through credit markets, spreading the pain more than expected? Who knows. That’s the problem with private markets. It’s hard to see where the risks lie and who might be left holding the bag.

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