Massive AI and cloud infrastructure spending by tech giants is flooding the market with new debt. For the first time since the 2008 crisis, this oversupply, not macroeconomic fears, is becoming a primary driver of market volatility and repricing risk for existing corporate bonds.

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.

Unlike equities, credit markets face a growing risk from the AI boom. As companies increasingly use debt instead of cash to finance AI and data center expansion, the rising supply of corporate bonds could pressure credit spreads to widen, even in a strong economy, echoing dynamics from the late 1990s tech bubble.

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.

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.

Beyond the long-term threat of AI disruption, highly leveraged, lower-quality software companies funded by private credit face a more immediate problem: a $65 billion wall of debt maturing by 2028. They must refinance this debt amid high uncertainty, creating significant near-term risk separate from AI's eventual impact.

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.