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Thoma Bravo's private equity firm is handing software company Medallia to creditors, wiping out $5.1B in equity. The failure highlights a dual threat: rising interest rates ballooning debt payments on leveraged buyouts, and AI startups rapidly disrupting the core business of established software companies.

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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.

A large concentration of private credit lending is in the software sector, particularly SaaS businesses. The rise of powerful AI tools that can replicate software services cheaply poses a direct threat to the viability of these companies, creating a hidden risk concentration within private credit portfolios where there are few hard assets to recover.

Private credit funds are exposed on two fronts: they are financing the massive debt rounds for AI infrastructure and also hold debt for traditional SaaS companies. As AI companies pitch a future where they render SaaS obsolete, it creates instability and default risk across these private credit portfolios.

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.

The traditional software buyout playbook relies on a stable terminal value multiple for exits. However, AI's ability to make existing code obsolete means long-term free cash flow projections are no longer reliable, rendering the leverage-based PE model fundamentally flawed.

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.

Recent financial distress in large, private equity-owned software companies is being misattributed to the threat of AI. The actual cause is over-leveraging when interest rates were low, followed by an inability to service that debt as rates rose and growth slowed. It's a credit problem, not a technology disruption problem.

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.