How to Manage the 4 Risks Hiding Inside Every AI-Heavy Portfolio

John O’Connell was recently published in Kiplinger, the third in his series on AI concentration risk, laying out four risks that could break the assumption holding up the AI buildout: that today’s spending gets paid back by tomorrow’s revenue. The four are demand risk, with the gap between AI spending and revenue running around $600 billion and widening; capital spending risk, since the hyperscalers’ budgets are quarterly guidance, not contracts; infrastructure bottleneck risk, where power, not chips, is now the binding constraint; and return-on-investment risk, with capex-to-revenue divergence already exceeding the late-1990s telecom buildout that preceded a multi-year correction. His advice is to look through every fund for exposure to the supply-chain layers rather than the familiar ticker, measure overlap across funds rather than within one, and stress-test each holding against a scenario where hyperscaler capex growth slows from 60% to 15%.