Michael Burry, has again warned that something may be wrong in the AI market. In the past, he correctly predicted the 2008 financial crash. Now, he believes the rush to build artificial intelligence, or AI, could turn into another bubble. He recently asked his followers on X an important question, “When does the spending for AI data center buildout actually end?” He also asked what happens to company earnings if that spending never slows down.

Why he is worried about AI data centers

Big technology companies are spending huge amounts of money to build AI data centers. These are large buildings filled with powerful computers that run AI systems. Burry says this AI buildout is “consuming” cash flow. That means companies are using up a lot of their extra money to build these centers.

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He believes this is forcing companies to handle money in ways they are not used to, such as borrowing more. He directed his comments at companies including Oracle, Google, Meta, Microsoft, Amazon, Nvidia, and Caterpillar.

How profits can look better than reality

Burry warned that companies might use “accounting tricks” if they feel enough pressure. This does not always mean fraud. It can mean using legal accounting methods to make profits look steady, even when cash is tight.

For example, when a company buys expensive computer equipment, it does not show the full cost immediately. Instead, it spreads the cost over many years. This is called depreciation. But in the fast-moving world of AI, that equipment may become outdated much sooner than expected.

Because of this, profits may look strong on paper, even though real money is being spent quickly. Later, companies may have to restate earnings, write them down, or see profits shrink as the real costs catch up.

Why borrowing could increase

Burry wrote, “The total revenues of Amazon, Apple, Alphabet, Microsoft, Meta, and Nvidia together do not make up $2 trillion. So you see why leverage is being used to build those data centers.”

Here he is saying that even though these companies are very large, their combined yearly sales are still smaller than the total amount being invested in AI infrastructure. So they may need to use leverage, which means borrowing money, to keep building.

He included Apple in this comparison as well.

A warning from history

Burry believes today’s AI boom looks similar to the internet boom around the year 2000. Back then, companies spent heavily on internet infrastructure. Stock prices rose very high, but when the dot-com bubble burst, markets fell sharply. By 2002, many stocks had lost more than 78 percent of their value.

He says today’s situation looks like “imitating the data connectivity buildout circa 2000.” His warning is that the same kind of crash could happen again if spending continues without clear returns.

What investors should watch

According to Burry, the key things to watch are what large tech companies say about future spending, especially capital expenditures. Investors should also look at whether free cash flow is improving or getting worse.

He also says people should pay attention to company reports. If there is a growing gap between how long equipment is actually useful and how long companies say it will last in their accounting, that could be a warning sign.

Disclaimer: This article provides factual analysis only and is not, and should not be construed as, an offer, solicitation, or recommendation to buy or sell securities. Investors must conduct their own independent due diligence and seek advice from a registered financial advisor in the respective jurisdiction.