The most likely outcome of the AI boom is a big fall
Like the dotcom boom of the late 1990s, AI is not paying off – despite huge investments being made in the hope of creating AI-based wealth

Two companies – Nvidia and Microsoft – each are worth more than $4 trillion. Together, that’s more than India’s and Japan’s combined annual output. Price is what you pay, as Warren Buffett put it. Value is what you get. Our question for today: how much value will investors get from the Magnificent Seven?
Our Law of Conservation of Value tells us that prices cannot stray too far or too long from value. And value depends on output. Investors ought to be able to look to a future stream of income and from it earn their money back, and more. Even in the dotcom bubble in 1999, the top firms were not as valuable or as concentrated as they are today. Nvidia, Microsoft, Alphabet, Apple, Meta, Tesla and Amazon – together, these firms make up a third of total US stock market value, an amount roughly equal to China’s GDP.
Part of the appeal of these stocks is that they are widely believed to be taking advantage of AI technology. In the case of Nvidia, of course, that is the central appeal. But the others are investing heavily in AI too. In 2024 and 2025, Meta, Amazon, Microsoft, Google and Tesla will put more than half a trillion into AI. The revenue from these investments is expected to be around $35 billion. Amazon, for example, has invested more than $100 billion, which is thought to generate an extra $5 billion in revenue.
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We don’t know how reliable or meaningful these figures are. What we do know is that they aren’t very impressive. As in the dotcom boom of the late 1990s, AI is not paying off. Huge investments are being made in the hope of creating AI-based wealth. But so far, the output doesn’t measure up.
You can go to ChatGPT, for example, and pay for the service. Many people use it occasionally – including us. But few pay for it – also including us. This would be fine, except that so much investment has gone into AI development that anything less than spectacular results will look like failure. One estimate, from Goldman Sachs, showed that the Magnificent Seven big tech stocks would have to produce $600 billion in extra annual revenue to make sense of their investment.
How will the AI boom end?
The appeal of the dotcom era was the idea that more information would lead to higher GDP growth rates with less need for capital investment.
Costly trial-and-error expansion would be replaced by less costly, more precise, knowledge-driven growth, or so it was believed. It didn’t work out that way. Productivity and growth rates generally softened throughout the 21st century. Capital investment went down. The internet/information revolution did not compensate for the decline; it seems to have made it worse. In the last half century, the rise in labour productivity in developed economies has declined from about 2% annually in the 1990s to 0.8% in the last decade, says the OECD think tank.
Will that change with AI? Probably not. The defining curse of the information revolution was too much information. It piled up. It got distorted and misinterpreted. It took time and money to store and sort. Much of it was false or useless. Now cometh AI, adding to the problem. Which leaves, at least for now, AI and the Magnificent Seven in an old-fashioned bubble. Stock prices are far higher than actual sales and profits can account for. So one way or another price and value will have to come back together. Some breakthrough might lead to a big burst of gains and growth. More likely is that stock prices will fall.
For more from Bill, see bonnerprivateresearch.com
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Bill Bonner is an American author of books and articles on economic and financial subjects. He is the founder of Agora Financial, as well as a co-founder of Bonner & Partners publishing.
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