Capital Is More Expensive for Companies Outside the AI Boom

UpTrajectory Review

Michael Mankins writes in Harvard Business Review that capital now carries a steeper price for companies outside the artificial intelligence boom. The available excerpt gives one sentence: the higher cost of capital shapes the economics of corporate strategy in three ways. The full article, one assumes, names those three ways and supports them with data on credit spreads, equity valuations, and the flow of investment toward AI-linked firms. We review what the headline and fragment tell us, and we flag plainly where the original likely does the heavy lifting.

A small-business operator does not need a finance degree to feel this story. Banks and investors now sort borrowers into two bins: firms that touch AI infrastructure, models, or deployment, and firms that do not. The first bin borrows cheaply and attracts equity; the second bin pays more for every dollar of debt and finds equity scarce. If you run a restaurant, a repair shop, or a regional distributor, you sit in the second bin. Your loan pricing, your lease terms, and your valuation multiple all reflect the market's hunger for AI exposure and its impatience with everything else.

The genuinely new point here is the widening spread between AI-adjacent and non-AI capital costs. For a decade, loose money flattened that spread; strategy teams could assume a uniform discount rate across industries. Mankins argues that assumption no longer holds. We agree with the direction and remain skeptical of any claim that the spread will persist at current levels; capital markets reprice narratives quickly, and a crowded AI trade can reverse. The article's value lies in forcing operators to test their own cost-of-capital assumptions rather than borrow last year's spreadsheet.

Second-order effects run through every corner of a small firm. Higher capital costs raise the hurdle rate for expansion, so projects that cleared the bar in 2021 now fail on paper. Owners who planned to fund growth with retained earnings face a subtler squeeze: customers and suppliers in AI-exposed sectors receive capital on better terms and can outbid you for talent, equipment, and real estate. The cost gap also changes who buys whom; cash-rich AI beneficiaries can acquire traditional businesses at multiples those businesses could never use to buy back. Expect consolidation in sectors the market labels legacy.

Watch two numbers each quarter: the spread between investment-grade yields for AI-heavy and AI-light industries, and the share of venture and corporate capital directed toward AI. If the spread narrows, the discount-rate gap will close and non-AI strategies regain room to breathe. If the spread widens, delay capital-intensive projects, renegotiate debt before renewal, and consider partnerships that give your firm a credible AI adjacency. Do not bolt on a chatbot and call it transformation; investors price genuine capability, not theater.

The action step is direct. Pull your current borrowing costs and compare them with the rates quoted to firms in your sector three years ago. If the gap against AI-linked peers exceeds two percentage points, treat capital as a scarce input: stage your investments, lease rather than buy where possible, and protect cash flow over headline growth. Mankins gives you the diagnosis; the prescription is yours to write.

“This affects the economics of their strategies in three ways.” — Harvard Business Review

Takeaway: Recheck your cost of capital now; if AI-linked peers borrow cheaper, stage investments and protect cash flow.