The AI Bubble Is Bigger Than You Think

It’s not just OpenAI that looks overhyped. There’s a whole mountain of sketchy financial engineering underneath.

https://prospect.org/2025/11/19/ai-bubble-bigger-than-you-think/


Source: Center for Public Enterprise

One thing I’ve been tracking this year is the areas where Wall Street and Silicon Valley are going to war. Tech firms clearly want to become banking apps and receive special charters, private equity and crypto are jostling for position in worker 401(k) plans, and the tech right in general wants to supplant big banks as the go-to director of conservative business policy. That’s all still going on. But in one area, Silicon Valley and Wall Street are in sync: conjuring up sketchy credit deals that are pointing us toward another financial crash.

Last month, the big focus was “round-tripping,” the way that sundry AI and tech companies were investing in their own customers—with Nvidia giving AI companies the investment necessary to buy their graphics processing units (GPUs), and so on. But there’s a lot more to this story, tangled up with yet another rebrand by the former masters of the universe, from “shadow banks” without proper regulation into something boring and neutral-sounding: private credit. Ever since the advent of financial regulation, there have been companies that have attempted to evade the rules with creative branding. Private credit companies are non-banks that are trying to rebrand into a name that doesn’t tell everyone they are unregulated lending vehicles.

The speculative financing of the artificial intelligence buildout is happening mostly in private credit, where assets under management hit $1.6 trillion in February and are likely higher today. The deals being made are perverse and irrational; there are huge mismatches between the life cycle of the assets being funded and the amount of time it will take to pay them off. Experts have been doing everything but picketing the stock exchange with signs that say “BUBBLE IN PROGRESS,” yet the country has so much sunk cost in the AI boom that the pathway feels inevitable. “We have sealed the deal on another financial crisis—the question is size,” said one former congressional staffer.

Related: The AI ouroboros

I will try to explain this as simply as I can. The build-out of computing power for AI needs about $2 trillion in annual revenue by the end of the decade to justify the current and planned investment. It’s an insane amount of money, nobody has it—nobody may ever have it—and so everything being constructed now, from the GPUs needed to train AI models to the data centers housing them to the energy supplying those data centers, needs some creative financing. Big Tech companies have large cash flows, but the trillions needed are too steep even for them. Venture capital isn’t that interested in funding infrastructure either; while the God in the machine that may result from the AI build-out has potential for supercharged returns, data centers and power plants, by themselves, won’t get you there.

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