NYU Professor Says Watch Smaller AI Stocks When The Shakeout Hits

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NYU’s Aswath Damodaran warns the next AI shakeout will hit smaller, undercapitalized firms hardest while the Magnificent Seven (Nvidia, Microsoft, Alphabet, Amazon, Meta, Apple, Tesla), which have spent tens of billions on AI infrastructure, have the cash flow and balance sheet strength to survive. He highlights sharply falling marginal returns on invested AI capital at Meta, Alphabet and Microsoft despite rising capex, signaling risk of a correction that could pressure niche AI names and influence tech funding, crypto fundraising and broader adoption dynamics.
In Brief
- Aswath Damodaran says AI's biggest players are financially protected, not smaller ones.
- NYU professor sees a shakeout risk building as capex outpaces returns at Big Tech.
- Meta, Alphabet, and Microsoft show falling returns on invested AI capital, he says.
Aswath Damodaran, known as Wall Street’s Dean of Valuation, says the next AI shakeout will hit smaller companies hardest. He says the Magnificent Seven have the cash flow and balance sheet strength to survive it.
In a new interview, Damodaran pointed to falling returns on invested AI capital at Meta, Alphabet, and Microsoft. He called the drop remarkable given the companies’ size.
Small AI Names Carry More Risk
The Magnificent Seven, Nvidia, Microsoft, Alphabet, Amazon, Meta, Apple, and Tesla, have spent tens of billions on AI infrastructure. Damodaran says their cash flow and debt capacity keep them out of trouble.
Smaller, less capitalized AI firms lack that same cushion, he warns. He points to the Situational Awareness hedge fund collapse as a sign of how quickly AI sentiment can shift.
“So I think when you see a shakeout in the AI space, it’s not so much the Mag-7 we should be watching, but the lesser companies.”
– Aswath Damodaran, NYU Stern School of Business
Falling Returns on AI Investment
The concern goes beyond mood. Damodaran tracks marginal return on invested capital, or income gained per new dollar of capex.
At Meta, Alphabet, and Microsoft, that ratio has fallen sharply even as spending keeps climbing. Damodaran says the size of the drop stands out given how large these firms already are.
The pattern echoes strain already hitting chipmakers after Micron’s sharp share drop rattled the memory sector. Not everyone reads the slowdown as a warning sign, though.
Tom Lee, for one, called the same AI capex fear signal bullish rather than alarming. He argues that widespread doubt about the AI trade suggests the cycle still has room to run.
Damodaran warns that unless hyperscalers post earnings that match their spending, a different kind of Big Tech will emerge. It would be more capital intensive and deliver lower returns.
Whether the correction spreads beyond niche AI names remains unclear. Much may depend on whether hyperscaler spending keeps outpacing earnings growth in the coming quarters.
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