Supervest Explores How AI Could Reshape Private Credit Investing

This is best read as a dispersion setup, not a broad AI macro call. The market should increasingly separate cash flows backed by labor substitution risk from those tied to physical execution and local demand; that favors service-heavy operators with low digital disintermediation risk and hurts lenders whose underwriting assumes stable white-collar headcount or sticky subscription renewals. The first-order beneficiary is not “AI” itself, but businesses that can use AI to cut SG&A without inviting a new competitor.

The real credit issue is timing: public software can rerate in weeks, but private credit pain shows up later through weaker sponsor exits, tighter amend-and-extend terms, and lower recovery expectations at refinancing. That suggests a 1-3 month window for valuation pressure in software-heavy baskets, followed by a 6-18 month risk that vintages originated at optimistic growth multiples need more structure, not just more spread. The market is underestimating how often efficiency gains become a bargaining chip for customers rather than permanent margin expansion for lenders.

Contrarian view: consensus is treating AI as uniformly positive for borrowers because it boosts productivity. What it may actually do is compress the value of the human-intensity moat that justified leverage in the first place, while leaving only the strongest software names with pricing power. The overdone part of the selloff is indiscriminate SaaS de-rating; the underdone part is private-credit spread widening in sponsor-backed tech and tech-enabled services where the refinancing story deteriorates before earnings do.