Is now a good time to buy artificial intelligence ETFs?
Investors assessing the top funds to invest in will likely consider buying one or two artificial intelligence (AI) ETFs, but could be forgiven for exercising caution.
There is a very valid argument that the AI boom is on borrowed time, making now an inopportune moment to buy AI stocks and funds. The valuations of its leading lights, not to mention its dimmer bulbs, are stretched to extremes.
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In the short run, this might not be sustainable. However, Ben Seager-Scott, chief investment officer at Forvis Mazars, advocates a new role for AI stocks and funds in investor portfolios.
“Investors allocating to this area for the first time aren’t exactly discovering a hidden gem, but equally the sustainability of growth in this area is pretty unknown, so it’s not obviously a terrible investment,” he tells MoneyWeek. He cites the maxim “we tend to overestimate the effect of technology in the short-term and underestimate the effect in the long-term” as potentially relevant to AI investing today.
“I don’t think [AI] is a thrilled tactical play, but [it] could still warrant a place in portfolios as part of a long-term thematic allocation.”
Within this context, AI ETFs can help investors gain targeted exposure while mitigating some of the risk associated with investing in individual AI stocks.
“Identifying future winners can be very difficult – it’s not always the obvious names that make it in the long-term,” says Seager-Scott. “If you’d have told me 20 years ago that mobile phones would be massive in the future I’d probably have loaded up on Nokia and Blackberry (Research in Motion back then) – not the niche Apple Mac maker or the boring Samsung TV maker.”
An ETF comprising a selection of AI stocks could, therefore, be a smart way for investors to seek longer term gains from the theme.
What kinds of AI ETF are available?
The first decision that applies to any ETF selection process is the active vs. passive debate. Actively-managed ETFs tend to charge higher fees than passive equivalents, but they offer the potential to beat the market through the judicious trades of their portfolio manager. This isn’t guaranteed to happen (and in fact, most studies show that active management tends to underperform rather than outperform), but it can potentially lead to outsize returns.
Not all passive AI ETFs are the same, either. The selection and rebalancing strategy of their benchmark index can make a big difference to their returns.
Index construction also impacts the extent to which an ETF can be considered a true reflection of its stated objective (in this instance, AI exposure).
“If it is too broad, you can just end up with a lot of generalist stocks and an index that is more driven by general global trends rather than AI specifically,” says Seager-Scott. “Whereas, if the index rules are too narrow, you can end up with a small number of obscure names that carry a lot of concentration risk and may not ultimately be the beneficiaries of the technology.”
As a demonstration of how it can differ even between four ETFs investing in the same theme, consider these four AI ETFs:
Swipe to scroll horizontally
ETF ticker
Active / passive
Fees (TER)
Price change*
INTL
Passive
0.40%
20.1%
AIAI
Passive
0.49%
31.9%
AIQU
Passive
0.40%
15.0%
ARKI
Active
0.75%
59.9%
(*Price changes over the 12 months to 9 December 2024, except ARKI which shows changes since listing, 19 April 2024, and AIQU which shows returns since listing on 12 September 2024.)
Let’s have a look at the pros and cons of each ETF and explore what they potentially offer an investors’ portfolio.
1. INTL: targeted AI exposure
The WisdomTree Artificial Intelligence UCITS ETF (LON:INTL) tracks the NASDAQ CTA Artificial Intelligence Index.
This index assesses a broad universe of stocks' relevance to three categories (AI enablers, engagers and enhancers), and selects 15 companies (reviewed twice annually) from each based on the degree of their relevance.
Enablers – the builders of AI components, like Nvidia (NASDAQ:NVDA) – comprise 50% of the index, while engagers (companies that develop AI-centric products) and enhancers (those that leverage AI, without it being core to their product offering) comprise 40% and 10% respectively.
The upshot of this is that INTL offers exposure that is directly tied to the relevance of stocks to the AI theme.
2. AIAI: quarterly rebalancing
The L&G Artificial Intelligence UCITS ETF (LON:AIAI) tracks the ROBO Global Artificial Intelligence Index. Like its Nasdaq counterpart, this index weights constituents based on their relevance to the AI theme.
However, it rebalances quarterly, meaning that there is twice as much buying and selling of the constituent stocks going on. Lots of investors like frequent rebalancing because it effectively automatically sells high, and buys low: assuming no change in relative AI relevance, stocks whose share prices have outperformed over the quarter will be sold, and those that have underperformed will be bought.
Though not for everyone (many investors prefer strategies that let outperformers run their course longer before taking profits), this makes AIAI an interesting option for investors that see the value in a quarterly rebalancing strategy.
3. AIQU: broad diversification
The Global X Artificial Intelligence UCITS ETF (LON:AIQU) is the laggard of this group, even accounting for it being the newest, gaining 15.0% since its inception compared to AIA’s 19.0%, INTL’s 23.1%% and ARKI’s 40.1% in the same period.
Its benchmark index, the Indxx Artificial Intelligence Index, uses a modified market-cap weighted approach that caps individual holdings at 3% and rebalances twice annually.
While this low cap could weigh on performance (by limiting the gains from individual outperformers), it does potentially make it appealing for investors worried about megacap concentration.
At the time of writing, Tesla (NASDAQ:TSLA) is the top holding, reflecting the gains the stock has made since the last rebalance in July, in light of strong third-quarter earnings results and optimism after CEO Elon Musk’s new bromantic partner, Donald Trump, was re-elected to the White House.
Besides Tesla, though, AIQU’s strategy gives mid-caps room to flourish. ServiceNow (NYSE:NOW) is its second holding, followed by former FAANG darling Netflix (NASDAQ:NFLX). Nvidia only just scrapes into the top ten.
As a diversification play, then, AIQU has some promise, but it’s unlikely to capture the kind of big moves that many AI investors hope for.
4. ARKI: actively-managed AI
Since it launched, the ARK Artificial Intelligence & Robotics UCITS ETF (LON:ARKI) has exemplified the (often unfulfilled) promise of active management.
While the ETF only listed in April, it has already raced ahead of its three passive competitors, gaining just under 60% (in the same period, AIAI gained 29.1% and INTL gained 19.1%). Investors holding the fund won’t mind an extra 35 basis points in fees when its returns are more than double that of the competition.
Of course, there is no guarantee that this will be the case over the long run. ARK funds have something of a boom-and-bust history.
However, any investors who want to hold onto the seat-of-your pants, short-term volatility that characterised the first stage of the AI boom might be interested in the fund, not just because of the potential outsize gains its active management strategy makes possible.
ARK’s CIO and founder, Cathie Wood, typically favours smaller, early-stage companies: top holding Palantir (NASDAQ:PLTR) currently has a market cap of $177.96 billion, while fifth holding Rocket Lab’s (NASDAQ:RKLB) is just $11.5 billion. Nvidia is there, but it’s a relatively small holding at 1.74% of the fund’s weight.
However, investors might want to heed Seager-Scott’s advice about selection criteria. Some of ARKI’s holdings, like Rocket Lab and Shopify (NYSE:SHOP), have only tenuous links to the AI/robotics theme that supposedly defines the fund. Besides volatility, another ARK trait is for Wood’s favourite stocks to appear in sometimes surprising funds.
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Dan is a financial journalist who, prior to joining MoneyWeek, spent five years writing for OPTO, an investment magazine focused on growth and technology stocks, ETFs and thematic investing.
Before becoming a writer, Dan spent six years working in talent acquisition in the tech sector, including for credit scoring start-up ClearScore where he first developed an interest in personal finance.
Dan studied Social Anthropology and Management at Sidney Sussex College and the Judge Business School, Cambridge University. Outside finance, he also enjoys travel writing, and has edited two published travel books.
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