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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.

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Companies with significant debt lack the cash flow to invest in transformational technologies like AI. This makes them highly vulnerable to disruption, similar to how leveraged retailers like Sears failed against innovators like Walmart during the e-commerce boom.

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.

A new risk is entering the AI capital stack: leverage. Entities are being created with high-debt financing (80% debt, 20% equity), creating 'leverage upon leverage.' This structure, combined with circular investments between major players, echoes the telecom bust of the late 90s and requires close monitoring.

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 AI growth seems organic, low interest rates encourage even healthy companies to take on excessive debt. This is happening now, with some AI-related firms seeing decreasing free cash flow as leverage increases. The private credit market is already showing signs of nervousness about this trend.

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.

Tech giants are no longer funding AI capital expenditures solely with their massive free cash flow. They are increasingly turning to debt issuance, which fundamentally alters their risk profile. This introduces default risk and requires a repricing of their credit spreads and equity valuations.

Roughly one-third of the private credit and syndicated loan markets consist of software LBOs financed before the AI boom. Goodwin argues this concentration is "horrendous portfolio construction." As AI disrupts business models, these highly levered portfolios face clustered defaults with poor recoveries, a risk many are ignoring.

Private Credit Risk Is Highest for Leveraged Firms Unable to Fund AI Innovation | RiffOn