The most significant risk in software-focused private credit isn't established companies but those underwritten on Annual Recurring Revenue (ARR) multiples instead of cash flow. These high-growth, non-cash-flowing businesses may never reach profitability if disrupted by AI, creating a major potential vulnerability.

While public software stocks have dropped 20-30% on fears of AI disruption, credit markets, particularly private credit, remain confident. Lenders are protected by low leverage multiples (1-6x EBITDA) and a substantial equity cushion, making them less sensitive to equity valuation shifts.

The "canary in the coal mine" for private credit isn't SaaS debt but any over-leveraged company. A firm burdened by debt repayments lacks the capital to invest in AI and automation, making it vulnerable to disruption by less-leveraged, more innovative competitors in any industry, not just software.

An expert warns of a "mini bubble" where private credit funds lent heavily to PE firms buying unprofitable software companies based on high ARR multiples. With falling valuations, AI disruption, and a wall of debt maturing, a wave of defaults and restructurings is imminent.

Software's heavy presence in leveraged loan (<15%) and private credit (>20%) portfolios makes these markets more vulnerable to AI disruption than high-yield bonds (<5%). This concentration risk is already visible, with the distressed universe of leveraged loans growing 50% year-to-date, a stress not yet seen in the bond market.

A significant portion of private credit portfolios consists of loans to software companies, which were underwritten based on predictable, recurring revenue. AI is now fundamentally disrupting these business models, threatening to devalue the very collateral that underpins billions of dollars in these 'safe' loans.

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 MAG7 companies fund AI spending with cash flow, the real danger is other firms using debt, especially private credit. This transforms potential corporate failures from isolated events into systemic risks that can cause broader economic ripple effects.

A significant portion of private credit is concentrated in software companies. Many of these loans were made when rates were low, often with high leverage and weak terms. The emergent threat of AI-driven disruption to their business models now adds a new layer of fundamental risk to this already vulnerable cohort.