NYU finance professor Damodaran warns an AI crash could hit harder than the dot-com bust

Aswath Damodaran, a finance professor at New York University, warns that a potential crash in the AI sector could be more painful than the bursting of the dot-com bubble around 2000.

In the podcast "Intangible Economy," he explains that unlike the dot-com era, the AI industry needs massive investments in physical infrastructure and much of it is financed with debt. If a correction hits, the damage wouldn't just fall on shareholders but could ripple out across society.

Damodaran also questions whether the AI business model can scale the way people expect. In his view, AI isn't a traditional software business. Costs don't automatically drop toward zero as more users come on board. Every additional use burns compute, similar to how Spotify pays for each stream.

That makes economies of scale far weaker than in Netflix's case, which Damodaran contrasts with Spotify: Netflix's high content costs get spread across a growing subscriber base, while Spotify pays per stream. Growth paired with thin margins could actually destroy value. Moreover, there's the risk of price erosion from Chinese competitors like Deepseek. Margins are already low.

Damodaran also warns about the bull case, because the business model would then be about replacing entire jobs, not selling AI as a tool. If AI actually delivers on this promise, "half of white-collar workers" would lose their jobs.

"The scary thing is the big stories you tell that can justify AI, if they come true, are going to create some insane costs for society that we better start thinking about right now," Damodaran says. He calls this scenario the "AI fever dream."

Big tech is entering unfamiliar territory

Damodaran says that he owns five of the seven so-called "Magnificent Seven" stocks, including Amazon, which he's held on and off since 1997. He says he has to accept that these companies are changing at a fundamental level because of their heavy AI investments. Instead of just tracking margins and new business lines, he now also has to analyze capital expenditures and depreciation.

For companies that used to be capital-light, that never mattered. These companies grew with minimal capital spending. Now they're building massive factories and infrastructure that will be depreciated over ten years but could be obsolete after five. "I'm not sure they really know what they're getting themselves into," Damodaran says.

Apple's cautious approach looks smarter to him. Many analysts have criticized Apple for not jumping in headfirst, but Damodaran sees it as a strength because "we undervalue restraint in business." Apple can sit back, watch others make mistakes, and learn from them instead of pouring billions into areas where it has no experience, Damodaran says.