AI Threatens Software Revenue, Pressuring Hercules Capital’s Borrower Mix and Private Credit

Hercules Capital’s borrower mix under pressure as AI threatens software revenue

Private credit lenders that finance technology and software companies face fresh stress as rapid advances in generative AI threaten incumbents’ business models, a development that hits firms such as Hercules Capital which lend heavily to venture-backed software and tech firms. The emergence of advanced models that perform complex professional tasks is increasing the risk that traditional software vendors see revenue erosion, putting pressure on cash flows that support loan repayments and covenants in the private credit market.

Hercules Capital’s portfolio sensitivity is notable because enterprise software accounts for a large share of business development company (BDC) deal activity—about 17% of U.S. BDC investments by deal count—and many private credit facilities backing technology deals are structured as illiquid unitranche loans. Those structures depend on predictable cash generation and can be hard to value or trade in stressed conditions, raising concerns about covenant compliance, liquidity shortfalls and the need for loan extensions or restructuring if borrowers’ revenues slow faster than expected.

Market participants and advisers warn that the AI-driven disruption may accelerate adaptation challenges for mid‑market software firms that are common Hercules borrowers. Analysts say the speed of adoption for AI tools could outpace a borrower’s ability to reprice products or rework go-to-market strategies, increasing default risk in a roughly $3 trillion private credit market. UBS and other forecasters outline scenarios in which private credit default rates could rise materially if disruption proves severe, adding another stressor to already strained loan portfolios that had seen liquidity and extension issues before the latest AI developments.

Wider industry implications

The immediate focus for Hercules and peer BDCs is heightened underwriting scrutiny, more active covenant monitoring and contingency planning for restructurings. Lenders may push for tighter documentation, more frequent reporting and covenant floors where practicable, while re-examining exposure to segments most vulnerable to rapid AI substitution.

Outlook for private credit managers

How quickly borrowers adapt and how aggressively managers act will determine near-term outcomes. If software companies pivot their product roadmaps and monetization to incorporate AI value, loan performance may stabilise; if not, private credit investors face greater credit work-outs, slower capital recycling and potential mark-to-market pressure on illiquid loan books.