Robert Thompson, CAIA
Principal/Sr. Director, Research – Flexible Capital
Recent advances in artificial intelligence (AI) are widely viewed as a direct threat to many legacy software providers. AI may create efficiency gains and margin expansion for certain companies, but it may also disrupt existing competitive moats and accelerate obsolescence for others. The pace of change has been rapid, and the range of outcomes remains uncertain. AI’s impact is likely to be felt across all public and private asset classes; this uncertainty is reflected in recent public equity market volatility. For private credit investors, the key question is not “AI winners vs. losers” in equity terms, but whether disruption alters cash-flow durability and, potentially, recovery values over a 5 year loan life.
This uncertainty has contributed to a sharp sell-off in segments of the public software equity market and has raised broader questions about valuation and durability within privately owned software companies. Software-as-a-service (SaaS) was a dominant theme in private equity investing over much of the last decade, and private credit capital helped fuel this growth.
SaaS business models historically offered attractive characteristics for lenders, including consistent recurring revenues, scalability through platform add-ons and acquisitions, sticky customer bases, and asset-light structures. These features supported strong underwriting narratives and meaningful capital inflows into direct lending strategies.
In this investment perspective, we examine how AI-driven disruption may affect private credit portfolios with significant software exposure, outline potential complications, and discuss how investors can thoughtfully navigate rising dispersion and stress within direct lending markets.
The SaaS Lending Boom
Private credit funds generally lend to private equity-backed companies, many of which are smaller than their publicly traded peers. When interest rates moved up in 2022, capital flowed aggressively into direct lending, compressing spreads and supporting borrower-friendly structures. As spreads compressed and structures loosened, the margin for error narrowed, making long-duration disruption risk more consequential today.
Software became one of the largest sector exposures across both private credit portfolios and publicly traded business development companies (BDCs). According to S&P, software & technology companies account for roughly 25% of the private credit market through year-end 2025. Investors have historically valued SaaS business models for:
- Consistent recurring revenues
- Scalability via platform add-ons and acquisitions
- Sticky customer bases
- Asset-light business models
However, the durability of these characteristics is now being reassessed. Publicly traded BDCs—which serve as the most liquid, real-time reflection of private credit sentiment—have experienced meaningful volatility year-to-date through mid-February. Public bank loan funds, which also tend to be overweight software and technology, have generally been more stable but have recently shown signs of modest weakness.
Potential Complications
Mispriced Risk
Private equity sponsors were aggressive in refinancing loans in recent years. Combined with a surge in direct lending capital, this dynamic compressed spreads across the software sector. Loans originated prior to 2024 likely did not contemplate AI as a meaningful business risk, potentially resulting in underpriced credit exposure.
Concentrated and Understated Exposure
Software exposure may be larger than headline allocations suggest. Industry classifications can obscure underlying business models. Companies categorized as “business services,” and certain segments within healthcare and financial services, are often fundamentally software-driven enterprises. As a result, true technology exposure in private credit portfolios may be understated.
Duration Mismatch
Most private credit loans carry five- to seven-year maturities. Businesses that appear insulated from AI disruption today may face competitive threats over the life of the loan. Forecasting the long-term impact of technological disruption is inherently difficult, increasing the importance of underwriting discipline and ongoing monitoring.
Recovery Risk in Asset-Light Models
Asset-light structures can enhance margins and cash flow in stable environments. However, in a stress scenario, recovery values may be lower, particularly if intellectual property loses relevance or value due to tech disruption. This asymmetry warrants careful consideration in downside underwriting.
Should Investors Be Worried?
In our view, panic is not warranted, but complacency is no longer rewarded. The market appears to be moving from broad beta-driven outcomes to manager skill and credit-driven dispersion. Direct lending was a highly popular strategy in recent years, and the industry is now experiencing a period of normalization. What had been a “rising tide lifts all boats” environment is evolving into one characterized by greater dispersion and rising stress.
Experienced managers with deep credit teams and restructuring capabilities are better positioned to navigate this transition. In our experience, high-quality direct lenders maintain frequent communication with portfolio companies and private equity sponsors, and financial monitoring has intensified in recent months.
It is also important to remember that lenders have meaningful tools at their disposal to help enhance returns and mitigate losses, including:
- Enforcing Covenants – Covenant breaches can provide lenders with leverage to influence cash allocation decisions, restrict discretionary spending, and protect enterprise value.
- Sponsor Liquidity Support – Private equity sponsors and lenders are generally aligned. In certain situations, fresh equity injections can stabilize liquidity and support business continuity.
- Loan Amendments – Loan amendments—such as paid-in-kind (PIK) interest, covenant resets, or refinancings—can provide short-term relief while compensating lenders with enhanced economics.
- Restructuring Pathways – In default scenarios, lenders may take ownership and pursue restructuring strategies to maximize recovery. While rare, experienced managers maintain dedicated restructuring teams and have navigated such outcomes before.
Key Considerations
Know What You Own
Every portfolio is unique. Exposure to software and technology varies widely by manager, vintage, fund structure, and borrower size. Diversification across managers can help mitigate concentration risk. However, overdiversification may dilute outcomes in an environment of rising dispersion, underscoring the importance of manager selection. Software exposure varies widely across funds, ranging from single-digit percentages to more than 40%.
Public vs. Private Signals
Publicly traded BDC performance does not always reflect the underlying performance of private portfolios. In many cases, private funds managed by the same sponsor may differ significantly in size, mandate, and vintage. Public BDC price movements often reflect shifts in investor sentiment rather than underlying credit performance.
Expect Some Bumps
Payment default rates in private credit have generally ranged from 1–2% since 2021, coinciding with the direct lending boom. However, covenant defaults, as measured by Lincon International, reached 3.2% as of September 30, 2025. We expect default rates to rise from these unusually low levels, and investors should anticipate individual credit losses. Importantly, the impact of isolated losses must be evaluated in the context of the broader portfolio’s income generation. Most private credit portfolios have hundreds of positions, dampening the impact of individual credit losses.
Conclusion
AI-driven disruption is adding a new dimension of risk to software-heavy private credit portfolios. While we expect increased dispersion and a gradual rise in defaults from historically low levels, we believe this environment should reward disciplined underwriting, strong documentation, and managers with proven restructuring experience.
Private credit remains a relevant allocation for many institutional investors, but selectivity is critical. We are actively engaging with managers, reviewing portfolio exposures, and stress-testing assumptions related to AI, sector concentration, and recovery values. We welcome the opportunity to work with clients to evaluate positioning and ensure private credit allocations remain aligned with long-term objectives.
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