The debate about AI right now is whether the spending is justified. The five largest US cloud and AI companies are guiding toward more than $635 billion in combined capital spending next year, most of it for AI infrastructure, and the skeptics have a real case on the economics.

That is not the question I care about. If you build or finance power generation, the one that matters is different. If AI investment corrects, what happens to the demand?

It holds. Most of it was never AI to begin with.

The IEA’s latest electricity outlook attributes only about half of projected US demand growth through 2030 to data centers. The other half is electrification, manufacturing moving back onshore, and the work of balancing a changing generation mix. None of that runs on AI capital cycles. It arrives whether or not the next training cluster gets built.

The supply side is already short. New projects are waiting years on transformers, switchgear, and generation. In a market that constrained, an AI correction does not leave a glut. It relieves pressure on a system that could not keep up with the non-AI demand on its own. That is the part the AI narrative misses. The exposure sits with the constraint, not the valuation cycle.

I worked through the full argument, the numbers behind it, and the two strongest objections, including why the dot-com fiber glut is the wrong comparison, in the new piece.

[Read the full article on alexmarshallenergy.com →]

— Alex Marshall