'If OpenAI Fails, We'll Have a Massive Correction': Steve Eisman Says Michael Burry Is Focusing on the Wrong AI Risk

Steve Eisman and Michael Burry became famous for making fortunes by betting against the US housing market before the 2008 financial crisis.

Now, the two Big Short investors are taking opposing views on the biggest threat to the AI boom, with Eisman arguing that Burry may be concentrating too heavily on chip depreciation while overlooking what he considers a far more dangerous weakness: the industry's dependence on OpenAI and Anthropic.

Burry has spent much of the past year warning that the extraordinary enthusiasm surrounding AI could eventually unravel. His concerns have included soaring spending on AI infrastructure, the accounting treatment of data-centre hardware, and whether hyperscalers are accurately reflecting the declining value of the chips powering the boom.

Eisman, however, believes the depreciation argument is not the immediate threat to the AI trade.

Burry's Take on AI Chip Depreciation

Burry has focused particularly on the rapidly increasing investment in advanced GPUs and other high-performance computing equipment needed to train and run AI models.

The explosion in data-centre spending has been a major tailwind for chipmakers such as Nvidia, while hyperscalers have poured billions of dollars into infrastructure to meet demand for AI computing capacity.

Burry has argued that the economics could look considerably less attractive if AI hardware becomes obsolete faster than companies' accounting schedules suggest.

Earlier this year, he predicted that leading hyperscalers could understate depreciation by more than $175 billion between 2026 and 2028. The argument is essentially that companies could be reporting stronger profits because expensive AI equipment is being depreciated over periods that may not fully reflect how quickly the technology loses economic value.

Eisman Pushes Back on Burry's Threat Assessment

Eisman does not necessarily dismiss the accounting issue. Instead, he argued that Burry's focus on depreciation misses the bigger picture because demand for AI computing remains exceptionally strong.

Speaking on the New Money podcast, Eisman said: 'With all due respect to Michael, I think his argument is too academic.'

'If AI succeeds because Anthropic and OpenAI grow like crazy, and the hyperscalers do well, it won't matter whether the depreciation schedule changed from three or four years to five or six years,' Eisman added.

In other words, Eisman's argument is that strong underlying demand could keep older AI hardware economically useful for longer, limiting the immediate damage from concerns over accounting assumptions.

'Where I think he is wrong, for the moment, is that there is such demand for chips right now that there is still huge demand for the older chips,' Eisman added.

Eisman Sees OpenAI as Achilles Heel of AI Trade

Despite challenging Burry's depreciation thesis, Eisman is far from dismissing the possibility of a major AI correction. However, his concern lies elsewhere.

Eisman has recently identified OpenAI and Anthropic as the potential weak points in the AI investment chain. He has described their importance as the 'Achilles' heel' of the AI trade because so much of the industry's growth expectations ultimately depend on AI companies successfully turning enormous infrastructure spending into sustainable demand and revenue.

That creates a different kind of risk from Burry's accounting argument. 'If OpenAI fails and the whole chain goes in reverse, we'll have a massive correction that has nothing to do with the depreciation schedule,' Eisman said.

The warning is significant because the AI boom is not simply a story about semiconductor sales. It increasingly depends on a broader ecosystem in which model developers, cloud providers, data-centre operators, and chipmakers are tied together by expectations of continued AI adoption and spending.

Eisman concluded that if leading AI companies fail to deliver the growth investors expect, that chain could weaken rapidly.