AI-Led Software Selloff Spilling into $1.5 Trillion U.S. Credit Market, Morgan Stanley Warns

This analysis is based on the Reuters report [1] published on February 10, 2026, citing Morgan Stanley research warning that artificial intelligence-driven concerns in the software sector are beginning to affect credit markets. The software industry’s significant exposure to the U.S. loan market—representing $235 billion of the total $1.5 trillion—positions this sector as a potential vulnerability point amid growing uncertainty about AI’s impact on traditional software business models [1].

The timing of this warning coincides with broader market volatility in technology-related equities. Recent market data [0] indicates that semiconductor stocks experienced significant fluctuations, with the SOXX index showing notable swings in early February 2026. On February 4, the Nasdaq declined 1.35%, only to reverse with a 1.79% gain on February 6, suggesting heightened investor uncertainty about the technology sector’s trajectory [0]. This equity market volatility appears to be extending into credit markets, where the software sector’s concentrated debt exposure raises concerns among institutional investors and lenders.

The Morgan Stanley analysis highlights several structural characteristics of software loans that amplify AI-related concerns. The software sector’s 16% share of the U.S. loan market is disproportionate to its economic output, reflecting the capital-intensive growth strategies employed by software companies and their private equity sponsors over recent years [1]. This concentration becomes particularly significant given that half of all software loans carry credit ratings of B- or below, substantially higher risk classifications compared to broader market averages [1].

Furthermore, the maturity profile of software debt presents a refinancing challenge. With 46% of software debt maturing within four years—compared to 35% for the broader loan market—and 30% of outstanding software loans coming due by 2028 versus 22% for the overall market, the sector faces a front-loaded maturity wall that could create pressure if AI disruption impacts borrower cash flows and refinancing capacity [1]. The prevalence of sponsor-backed loans, at 78% of the software loan segment, means private equity firms will face significant decisions regarding portfolio company capitalization and potential additional equity injections [1].

The private credit market faces elevated exposure to this sector-specific risk. CNBC reporting [2] indicates that private credit worries have resurfaced in the $3 trillion market as AI fears intensify, with lenders who significantly increased software exposure since 2020 potentially having underestimated disruption risks. Asset managers with private credit franchises have already seen stock price reactions to these concerns, suggesting the market is pricing in potential credit quality deterioration [2].

T. Rowe Price analysis [3] provides additional context on how markets are weighing AI’s impact on the software sector, noting that enterprise value to free cash flow metrics and the “rule of 40” financial health threshold are receiving increased scrutiny. Companies meeting the rule of 40—achieving revenue growth plus profitability margin of at least 40%—may prove more resilient to AI disruption, while those failing this benchmark face greater vulnerability [3]. High-yield software bonds have shown weakness alongside loan valuations, indicating broader credit market contagion from software sector concerns [3].

Morgan Stanley’s assessment, while highlighting concerns, maintains a measured outlook on default risk. The research note explicitly states that “continued price volatility in loans” is expected, but “a near-term spike in defaults is unlikely” [1]. This distinction between price volatility and fundamental credit deterioration is significant for investors calibrating risk exposure.

The differentiation between AI-vulnerable and AI-adapted software companies represents a key analytical framework for credit assessment [2]. Not all software companies face equal disruption risk—those with strong AI adaptation strategies, established customer relationships, and sustainable unit economics may prove resilient. The “rule of 40” criterion serves as one measurable indicator of financial health that correlates with operational resilience [3].

: The software sector’s 16% share of the U.S. loan market, combined with its lower credit rating profile (50% at B- or below), creates concentrated risk exposure for private credit lenders who have aggressively expanded in this segment since 2020. This concentration is particularly relevant given the $3 trillion private credit market’s overall growth and the sector-specific nature of AI disruption concerns.

: The front-loaded maturity profile of software debt—with 30% of loans coming due by 2028—creates a potential refinancing vulnerability. If AI disruption impacts software company cash flows or if lenders tighten underwriting standards in response to sector concerns, borrowers may face challenging refinancing conditions. Private equity sponsors, holding 78% of software loans, will bear significant responsibility for addressing these maturities.

: The correlation between semiconductor equity volatility (Nasdaq’s 1.35% decline on February 4 reversing to a 1.79% gain on February 6) [0] and credit market concerns suggests increasing cross-market transmission of AI fears. This spillover effect indicates that credit investors cannot assess software sector risk in isolation from equity market dynamics.

: The predominance of lower-rated loans in the software sector (50% at B- or below) means that adverse valuation moves have proportionally larger impact on portfolio credit metrics and potential covenant compliance. Lower-rated credits also face steeper yield spreads during periods of market stress, potentially accelerating price deterioration.

: Software companies with debt coming due between 2026 and 2028 face heightened refinancing risk. If AI concerns persist or intensify, lenders may impose stricter terms, require additional equity cushions, or reduce commitments, potentially forcing borrowers into distressed situations. The 46% of software debt maturing within four years, compared to 35% for the broader market, underscores this concentration [1].

: Lenders with significant software exposure may face earnings pressure from mark-to-market losses on loan portfolios and potentially higher provisions for credit losses. The stock price reactions observed among asset managers with private credit franchises suggest the market is already factoring in some of these concerns [2].

: With 78% of software loans sponsor-backed, private equity firms may face elevated capital calls to support portfolio company refinancing. This could strain limited partner capital commitments and potentially slow deployment into new investments.

: The fundamental risk stems from uncertainty about the pace and depth of AI disruption to traditional software business models. If AI tools (particularly large language models and generative AI applications) erode software company competitive positions more rapidly than anticipated, credit quality deterioration could accelerate beyond current projections.

: Price volatility in software loans may create buying opportunities for investors with higher risk tolerance and strong credit analysis capabilities. Differentiated analysis focusing on AI-adapted companies meeting the “rule of 40” threshold could identify relative value [3].

: Credit market stress typically creates opportunities for well-capitalized lenders to gain market share from weakened competitors. Banks and direct lenders with limited software exposure may benefit from displaced borrower relationships.

: Software companies facing AI disruption and refinancing challenges will likely require advisory services for strategic repositioning and capital structure optimization, creating revenue opportunities for financial advisors and consultants.

: Priority monitoring of software loan price movements and private credit lender commentary during upcoming earnings calls will provide early indicators of actual credit impact versus market pricing [1].

: The maturity wall approaching between 2026 and 2028 represents the highest-risk window for refinancing stress. Portfolio review and proactive sponsor dialogue during this period will be critical for managing exposure [1].

: AI disruption impact on software business models will likely crystallize over a longer horizon, with successful adaptation strategies separating resilient from vulnerable credits.

: Software loans total approximately $235 billion, representing 16% of the $1.5 trillion U.S. loan market [1]. This concentration positions the software sector as a material source of credit market risk amid AI disruption concerns.

: 50% of software loans carry “B- or lower” credit ratings, indicating elevated default risk profiles compared to broader market averages [1]. This lower rating distribution amplifies vulnerability to adverse market conditions.

: Software debt exhibits a front-loaded maturity profile, with 46% maturing within four years (versus 35% for the broader market) and 30% coming due by 2028 (versus 22% overall) [1]. This structure creates concentrated refinancing pressure in the near-to-medium term.

: 78% of software loans are backed by private equity sponsors, indicating significant alignment of interests and potential capital resources to address refinancing challenges [1].

: The research note anticipates continued price volatility in software loans but does not project a near-term spike in defaults, suggesting the risk is currently more reflective of pricing and market sentiment than fundamental credit deterioration [1].

: Not all software credits face equal risk; companies meeting the “rule of 40” financial health threshold and demonstrating AI adaptation capabilities may prove more resilient to sector disruption [3].

: Recent semiconductor equity volatility (SOXX index fluctuations) and asset manager stock price reactions suggest the market is actively processing AI-related concerns across both equity and credit markets [0][2].