Private Equity Software Deal Slowdown: AI Risks Reshape Investment Landscape

This analysis examines the sustained decline in private equity and venture capital investment in application software, driven by escalating concerns about artificial intelligence’s potential to disrupt software business models. Deal volume has decreased for at least three consecutive years, with global application software transactions falling 21% in 2025 to 3,665 deals from 4,638 in 2024 [2]. Private equity-specific software deals declined 34% to 240 transactions [2]. The February 2026 tech selloff, which erased approximately $1 trillion from software stocks alone, intensified scrutiny on alternative asset managers’ exposure to the sector [4]. This development has significant implications for private credit lenders, limited partners, and portfolio companies navigating the AI transformation.

The private equity and venture capital industry’s retreat from application software investments represents a fundamental reassessment of sector fundamentals. Total PE and VC-backed application software deals reached 3,665 globally in 2025, marking a 21% decline from 4,638 deals recorded in 2024 [2]. The contraction is even more pronounced among pure private equity transactions, which fell approximately 34% to 240 deals in 2025 from 365 deals in the preceding year [2].

This slowdown reflects a multi-year trend accelerated by growing recognition that artificial intelligence poses existential risks to traditional software-as-a-service (SaaS) business models. The release of new AI tools by Anthropic in early February 2026 served as a catalyst for the most significant market correction in recent memory, demonstrating how quickly AI capabilities can render existing software solutions obsolete [4]. Companies can now automate functions—including customer support and legal services—that previously required dedicated software solutions, fundamentally undermining the value proposition of incumbent software providers.

The software sector has experienced substantial valuation contraction across both public and private markets. PE-backed SaaS company valuation multiples declined from 24× earnings in 2024 to 18× in 2025—a 25% reduction in valuation within a single year [0]. This compression reflects investor reassessment of growth durability in an environment where the marginal cost of software is rapidly collapsing due to AI capabilities.

The February 2026 technology selloff demonstrated the severity of this repricing, with software stocks bearing the disproportionate burden of the correction. Shares of major asset managers with large private credit franchises fell significantly during this period: Ares Management declined 12%, Blue Owl more than 8%, KKR approximately 10%, and TPG roughly 7% [3]. These declines reflect market concerns about the quality of underlying loan assets in private credit portfolios heavily weighted toward software companies.

The concentration of private credit exposure to the software sector creates elevated systemic concerns. Software represents the largest borrower group for private credit lenders since 2020, with many of the largest-ever unitranche loans issued to software and technology companies [3]. Approximately 20% of outstanding loans from private direct lenders are tied to software companies, while software accounts for roughly 17% of U.S. Business Development Company investments by deal count—second only to commercial services [0][3].

Analysts estimate that 25-35% of the entire private credit market is exposed to AI disruption risk, with software specifically representing a material portion of this exposure [0]. UBS Group’s stress tests project that in an aggressive AI disruption scenario, U.S. private credit default rates could climb to 13%, compared to 8% for leveraged loans and 4% for high-yield bonds [3]. These projections have prompted intensified scrutiny of loan portfolio quality among private credit investors.

The industry faces mounting pressure from limited partners seeking liquidity amid constrained exit opportunities. Approximately 40% of buyout net asset value is more than seven years old, with an estimated $100 billion exit backlog [0]. The secondary market has emerged as the primary liquidity outlet, reaching $226 billion in 2025—a 41% increase year-over-year—with $120 billion in LP-led transactions and $106 billion in GP-led transactions [0].

Buyout stakes are currently trading at approximately 94% of NAV, compared to less than 90% during the 2022 market trough, indicating elevated but not extreme discount levels [0]. However, as more sellers enter the market seeking liquidity, discounts may widen further, particularly for software-related assets perceived as vulnerable to AI disruption.

The anticipated benefits of AI integration have proven largely elusive for software companies, undermining the growth narratives that previously justified premium valuations. Only 12% of companies report both revenue gains and cost reductions from AI implementations, while approximately 95% of generative AI pilots fail to achieve production-scale deployment [0]. This disconnect between expectation and reality has contributed to the sector’s revaluation.

Among companies successfully implementing AI, productivity gains are substantial but create their own challenges. Studies show up to 30% increase in coding productivity, which could reduce developer headcount by approximately 23% per company [0]. While this improves margins, it simultaneously reduces the revenue base for software providers whose business models depend on seat-based licensing.

Private equity firms are actively reallocating capital from application software toward physical AI infrastructure. Brookfield committed $9.9 billion to a Swedish data center and announced a $25 billion U.S. AI-workload partnership, while Blackstone acquired AirTrunk for $16 billion in Q3 2024 [0]. MGX, Abu Dhabi’s sovereign wealth entity, is positioning 2025-2026 as a growth window for AI-infrastructure deals [0].

This shift reflects a fundamental reassessment of where value creation will occur in the technology sector. Rather than investing in application layers vulnerable to AI disruption, private equity firms increasingly favor infrastructure plays—data centers, compute capacity, and networking—that benefit from rising AI demand regardless of which software applications ultimately succeed.

Despite valuation concerns, private equity continues integrating AI into deal workflows. Approximately 86% of organizations have integrated generative AI into M&A processes, while 88% of PE firms have invested more than $1 million in generative AI capabilities [0]. This adoption reflects both operational efficiency pursuits and competitive necessity as firms seek to identify AI-vulnerable portfolio companies and assess acquisition targets’ competitive positioning.

1. Default Rate Escalation
   : Projected default rates of up to 13% in aggressive AI disruption scenarios represent significant credit risk for private credit lenders [3].

2. Valuation Volatility
   : Continued multiple compression could trigger margin calls and covenant breaches in leveraged loan portfolios.

3. Exit Timing Uncertainty
   : The $100 billion exit backlog may take years to clear, particularly for assets requiring premium valuations.

4. Competitive Displacement
   : Software companies slow to adapt to AI-native architectures face existential threats.

5. Concentration Risk
   : The significant exposure of private credit portfolios to software creates undiversified risk profiles.

1. Secondary Market Discounts
   : Elevated secondary market activity ($226 billion in 2025) provides liquidity opportunities for investors with longer time horizons [0].

2. Infrastructure Investments
   : Data center and AI infrastructure acquisitions offer exposure to secular AI demand growth.

3. AI-Native Software Leaders
   : Companies successfully navigating the AI transition may emerge as sector leaders with strengthened competitive positions.

4. Distressed Acquisitions
   : Well-capitalized firms may acquire distressed competitors at attractive valuations.

The private equity industry’s retreat from application software investments reflects fundamental concerns about AI’s disruptive potential on software business models. Deal volume has declined for three consecutive years, with PE software deals falling 34% in 2025 [2]. The February 2026 tech selloff, which erased $1 trillion from software stocks, intensified concerns about AI disruption risks. Private credit exposure of 20-25% to software creates systemic concerns, with potential default rates projected at 13% in aggressive AI scenarios [3].

PE firms have deployed approximately $440 billion across more than 1,900 software companies over the decade ending 2025, creating substantial legacy exposure [0]. Valuation multiples have contracted significantly, with SaaS companies declining from 24× to 18× earnings in just one year [0]. The industry faces a $100 billion exit backlog while only 12% of companies report achieving both revenue gains and cost reductions from AI implementations [0].