Oct 22, 2026 · 28 min
AI’s trillion-dollar buildout faces a revenue reckoning
AI adoption is slowing: ‘There’s no use case for frontier AI’ | Dean Baker
If frontier AI cannot generate exceptional profits, the correction could reshape data-center ownership, tech valuations, and antitrust policy.
- 1AI infrastructure spending is expanding far faster than credible revenue, while adoption and productivity gains remain limited.
- 2OpenAI and Anthropic face enormous compute commitments that could force acquisitions if growth and profitability fail to materialize.
- 3A correction may preserve useful infrastructure but concentrate cloud computing among hyperscalers and intensify antitrust concerns.
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Baker explains why even breaking even—or earning a conventional return—could still send AI stocks sharply lower because valuations require much larger profits.
The brief
Dean Baker argues that an $8.5 trillion AI buildout has no credible revenue base, especially when major consumer offerings remain free and adoption is slowing.
Gartner’s forecast suggests the industry may be more than twice its sustainable size, leaving data centers, GPUs, and NeoCloud companies exposed to a demand shortfall.
CoreWeave becomes a warning sign: falling shares, rising bond yields, heavy borrowing, and insider sales point to the financial strain behind AI infrastructure.
Baker expects a correction resembling the technology bubble’s aftermath, with useful infrastructure surviving even as speculative projects and weaker providers disappear.
OpenAI and Anthropic could eventually be acquired by hyperscalers if they cannot fund hundreds of billions in compute commitments or deliver extraordinary returns.
The skeptics could be wrong if frontier models prove dramatically better than cheaper systems, but Baker expects that productivity payoff later than investors do.
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