Private credit, a booming financial sector, faces an unmodeled risk from AI-driven job displacement. Current risk models aren't designed for a scenario where high-FICO-score, white-collar professionals—the core of many consumer loan portfolios—face widespread income disruption. This represents a potential systemic vulnerability.

Software, once a defensive haven for credit investors, faces a major threat from AI. AI's ability to standardize data and workflows could disrupt legacy SaaS companies, making the 30% of direct lending portfolios concentrated in software a significant, overlooked risk.

Private equity firms, which heavily invested in software companies for their stable earnings, are now in a bind. The AI threat devalues these assets and complicates exits, forcing them away from traditional IPOs and toward more complex M&A strategies.

Unlike prior tech revolutions funded mainly by equity, the AI infrastructure build-out is increasingly reliant on debt. This blurs the line between speculative growth capital (equity) and financing for predictable cash flows (debt), magnifying potential losses and increasing systemic failure risk if the AI boom falters.

Unlike the public equity markets, software exposure in credit markets is concentrated in private, not public, companies. An estimated 80% of these issuers are private, and 50% are rated B- or lower, creating a unique and more challenging risk profile due to lower credit quality and less transparency.

When evaluating software loans, Blackstone moves beyond financials to product underwriting. Its investment committee uses a specific scorecard to assess a company's risk of AI disruption, how embedded its product is in workflows, and how its technology stacks up, demonstrating a structured approach to modern threats.

Private credit funds have taken massive market share by heavily lending to SaaS companies. This concentration, often 30-40% of public BDC portfolios, now poses a significant, underappreciated risk as AI threatens to disintermediate the cash flows of these legacy software businesses.

While many firms are just now reacting to AI's impact, major credit investors like KKR have been actively underwriting AI-driven business model risk for nearly six years. This proactive, long-term approach to assessing technological disruption is a core part of their due diligence process, not a recent development.

Unlike the dot-com bubble's weak issuers, the current AI debt boom is driven by investment-grade giants. However, the risk is that these stable companies are using debt to finance speculative, 'equity-like' technology ventures, a concerning trend for credit investors.