Software Sell-Off: Framing Concerns About Private Credit

But is this a true disruption story, or a misreading of where value will ultimately accrue?

This paper dissects the four core elements behind the AI software disruption thesis, while offering insights into AI-specific safeguards that underwriters can apply to mitigate risk. While certain AI disruption risks are valid in a narrow context, many are overstated, in our view, particularly for mission-critical, enterprise-grade software systems where durability, compliance, proprietary data and integration depth remain paramount.

Rather than signaling decline, AI may act as a net-positive tailwind for well-positioned software incumbents—expanding the total addressable market (TAM), enhancing product stickiness, and unlocking new pathways to monetization. Meanwhile, outside of sentiment driven indicators, credit and equity fundamentals have emerged from the latest quarter on a solid footing.

Agentic AI can be a TAM Expander for Software

^{Risk Considerations
Alternative investments are speculative, involve a high degree of risk, are highly illiquid, typically have higher fees than other investments, and may engage in the use of leverage, short sales, and derivatives, which may increase the risk of investment loss. These investments are designed for investors who understand and are willing to accept these risks. Performance may be volatile, and an investor could lose all or a substantial portion of its investment.}

^{There is no guarantee that any investment strategy will work under all market conditions, and each investor should evaluate their ability to invest for the long-term, especially during periods of downturn in the market.}