The rapid proliferation of generative artificial intelligence is casting a long shadow over the $3 trillion private credit market, as investors and analysts warn that the technology could destabilize the software sector—a traditional cornerstone of private lending. Once considered a safe haven of recurring revenue and high margins, software companies are now facing an existential challenge that threatens to trigger a wave of defaults among debt-laden firms struggling to adapt to the new technological landscape.
The Software Stronghold Under Siege
For years, private credit funds have aggressively deployed capital into software-as-a-service (SaaS) providers, drawn by their predictable cash flows and “sticky” customer bases. However, the emergence of AI-driven automation is fundamentally altering the competitive landscape. Legacy software providers that fail to integrate advanced AI capabilities risk rapid obsolescence, while others face the prospect of shrinking contract values as AI increases efficiency and reduces the need for traditional per-seat licensing models.
Rising Default Risks and Valuation Pressures
This shift has introduced a sophisticated layer of credit risk that was largely absent during the previous decade of tech expansion. As AI lowers the barriers to entry for nimble new competitors, established firms burdened by significant debt loads may find their interest coverage ratios squeezed. Market observers are increasingly concerned that the “valuation cushion” that previously protected lenders is eroding, leaving private credit portfolios vulnerable to sudden downgrades and restructuring demands if cash flows begin to falter.
A New Era of Due Diligence
In response to these emerging threats, top-tier private credit managers are overhauling their underwriting processes to account for technological disruption. The focus has shifted from simple EBITDA growth to a rigorous assessment of a borrower’s “AI defensibility.” Lenders are now scrutinizing whether a company’s product suite can be easily replicated by large language models or if the firm possesses proprietary data that provides a sustainable competitive moat. As the industry grapples with these headwinds, the divide between AI winners and losers is expected to become the primary driver of credit performance in the coming years.
