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The crowding-out story is plausible—and especially vulnerable to motivated reasoning.

ContestedNot scoredmatched cost-of-capital series still required

What the evidence supports

AI infrastructure absorbs very large corporate and project-finance budgets, but a claim that it raises everyone else’s cost of capital needs a matched counterfactual across rates, credit quality and investment categories.

Mechanism
Hyperscalers can redirect internal cash; developers and utilities can issue debt or seek project finance. The macro effect depends on savings, monetary policy and whether AI investment expands future capacity.
Who pays—or gains
Potentially other borrowers through higher hurdle rates or deferred budgets. Investors and suppliers benefit when capital moves toward higher expected returns.
Binding constraint
A transparent comparison group and separation of AI demand from the interest-rate cycle.
Strongest caveat
The editor is a partner in Vellum Capital, a crypto fund that could benefit from an AI-crowding narrative. This series therefore receives the site’s most conservative publication threshold.
What would change the grade
Publish only after a preregistered matched series and external methodological review.

Evidence file

Primary and first-party sources

  1. GE Vernova first-quarter 2026 financial resultsGE VernovaPublished 2026-04-22 · checked 2026-07-16
  2. About David VekslerDavid VekslerPublished current · checked 2026-07-16