AI Shakeout Will Hit Smaller Firms Hardest, Says NYU Valuation Expert

Aswath Damodaran, known as Wall Street's Dean of Valuation and a professor at NYU Stern School of Business, has issued a stark warning about the AI industry's near-term trajectory. In a recent interview, he argued that when an inevitable shakeout hits the AI sector, it will devastate smaller, less capitalized firms while the Magnificent Seven—Nvidia, Microsoft, Alphabet, Amazon, Meta, Apple, and Tesla—will survive largely intact. The reason is financial: the Magnificent Seven have spent tens of billions on AI infrastructure and possess the cash flow and debt capacity to weather downturns that would crush underfunded competitors.

Damodaran's concern goes beyond sentiment or temporary setbacks. He has been tracking what he calls the marginal return on invested capital—the income gained per new dollar of capital spending—and has found a troubling pattern at Meta, Alphabet, and Microsoft. That ratio has fallen sharply even as these companies have continued to increase their spending. What makes this drop remarkable, Damodaran emphasizes, is that it is occurring at companies of such massive scale. The implication is that the return on each incremental dollar of AI investment is diminishing, even for the world's largest technology firms. This pattern mirrors stress already visible in the chipmaker sector, where Micron's sharp share drop rattled the memory market. Damodaran also points to the collapse of the Situational Awareness hedge fund as a sign of how quickly sentiment in AI can reverse.

Damodaran stated plainly: "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." His overarching concern is that unless hyperscalers deliver earnings that match their spending, the composition of Big Tech will shift toward companies that are more capital intensive and deliver lower returns. Not all observers share this view. Tom Lee, for instance, has characterized the same AI capital spending concern as bullish rather than alarming, arguing that widespread doubt about the AI trade suggests the market cycle still has room to run. The resolution will likely depend on whether hyperscaler spending continues to outpace earnings growth in the quarters ahead.