KBRA Releases Research – Private Credit: Deep Dive on AI and Software

NEW YORK--(BUSINESS WIRE)--KBRA releases research examining the impact of artificial intelligence (AI) on software and private credit portfolios.

In KBRA’s view, AI poses diffuse and manageable credit risks to software companies held by direct lenders. While some sponsor-backed borrowers with near-term maturities and structural exposure to AI disruption may face significant pressure—contributing to a modest increase in overall default rates—we find that most software-adjacent borrowers have business models, financial flexibility, and sufficient time to navigate the risks and opportunities presented by AI.

Although AI-related disruption may result in idiosyncratic stress for certain companies, sponsors, and lenders, we believe any resulting losses are likely to be absorbed by KBRA-rated direct lending entities and transactions without significant ratings migration. We expect the primary transmission of these risks to be reflected in increasingly differentiated returns across private credit investment vehicles.

Our view is that broader macroeconomic headwinds—including a prolonged Middle East conflict, elevated energy prices, persistent inflation, ongoing supply chain disruptions, and a higher-for-longer interest rate environment—pose a greater near-term risk to credit conditions than AI.

In this report, we conduct a deeper analysis of 495 companies across Software (415), Information and Telecommunications (40), and Internet and Data Services (40) (collectively, the Software and Technology cohort, which represents approximately 20% of our portfolio of more than 2,400 unique global middle market sponsor-backed borrowers). We present our framework for categorizing each company’s relative exposure to AI, highlighting key factors that may influence probability of default, with a focus on borrowers facing near-term debt maturities.

Key Takeaways

• AI-related disruption is likely to unfold gradually, but lender and sponsor behavior has already been shifted by AI uncertainty. For example, KBRA has observed lenders requiring additional covenants, increasing loan spreads by as much as 100 basis points (bps) or more, and, in some cases, demonstrating an unwillingness to extend maturities for underperforming companies or those viewed as more vulnerable to disruption from the new technology.
• Notably, the 165 companies that KBRA qualitatively identified as having relatively high AI risk already exhibit the weakest median financial profile within the Software and Technology cohort. This subset ranks among the weakest across all sectors in revenue growth and includes one of the highest shares of companies with declining sales. Their operating performance more closely resembles that of lower credit quality sectors such as Chemicals, Containers, Metals, Materials, and Consumer Retail. This underperformance suggests that sponsors and lenders are likely aware of these risks and are actively managing these exposures.
• In addition, 25% (41 companies) of the higher AI risk group have near-term maturities (defined as before the end of Q2 2027), representing one of the highest proportions across all sectors. This compares with 19% of the 2,416 borrowers assessed in 2025.
• The potential impact of these 41 companies on the KBRA Middle Market Default Monitor (KMDM)—our forward-looking measure of borrowers in payment default or at risk of default absent sponsor or lender intervention—appears contained. In a hypothetical scenario where all 41 companies default, the KMDM would increase to 4.8% from 3.4% by count and to 2.9% from 2.0% by value.
• We view these findings as strong evidence that widespread AI-driven defaults are unlikely and remain well within the risk tolerance of KBRA-rated direct lending vehicles. The 41 loans are distributed across more than 90 KBRA-rated vehicles managed by 28 direct lenders, with a median aggregate exposure per vehicle of less than 2.5%. These companies are also backed by 34 unique sponsors. This level of diversification should mitigate the impact of any AI-related stress on individual managers. Accordingly, we do not expect significant ratings migration among KBRA-rated direct lending vehicles.
• Sponsor support will remain a key differentiator, though the extent of support will depend on confidence in each company’s business model defensiveness, valuation, and broader industry headwinds. AI-related uncertainty, increased technology investment requirements, and lower valuation multiples in public and private software markets may further pressure valuations or delay exits and reduce sponsors’ willingness to provide incremental capital or deleverage portfolio company balance sheets.
• Based on discussions with direct lenders, KBRA understands that key performance indicators remain broadly stable. However, lenders are observing early signs of AI-driven impacts, including shifts in customer behavior, longer sales cycles, and budget reallocation toward AI initiatives. These trends are contributing to slower growth and potential margin pressure. As these dynamics develop, lenders are preparing for a modest increase in defaults.

Click here to view the report.

Recent Publications

• Private Credit: Framing AI and Software Risk
• Private Credit: Recurring Revenue Loans Performance Update
• Private Credit: Q4 2025 Middle Market Borrower Surveillance Compendium: Stability at the Median, Stress at the Margins
• Private Credit: Lessons From 2025's At-Risk Cohort
• Private Credit: 2026 Outlook

About KBRA

KBRA, one of the major credit rating agencies, is registered in the U.S., EU, and the UK. KBRA is recognized as a Qualified Rating Agency in Taiwan, and is also a Designated Rating Organization for structured finance ratings in Canada. As a full-service credit rating agency, investors can use KBRA ratings for regulatory capital purposes in multiple jurisdictions.

Doc ID: 1013867