Forvis Mazars, LLP, one of the largest public accounting and consulting firms in the United States, today announced the release of a new report examining the impact of AI adoption on the SaaS sector, produced in partnership with PitchBook. The report, “AI’s Impact on SaaS: Enterprise Adoption, Integration Strategies, and the New Cybersecurity Frontier,” examines private equity (PE) dealmaking trends across the global software-as-a-service (SaaS) landscape during the second half of 2025, with a particular focus on how artificial intelligence (AI) is reshaping capital allocation, operating assumptions, and exit readiness among investors during 2026.
Findings from the second-half analysis show that enterprise SaaS remains a dominant theme in private equity investing, but with a marked shift toward fewer, larger transactions. Capital continued to flow into SaaS through late 2025 even as deal volume declined, reflecting greater concentration among platforms best positioned for enterprise AI adoption.
“AI has fundamentally altered how private equity firms evaluate SaaS businesses, from underwriting assumptions to exit timing,” said Ricardo Martinez, partner and national industry leader for technology and software at Forvis Mazars. “What we’re seeing is a market that still believes strongly in enterprise SaaS, but one that is far more selective. Success now depends on how effectively management teams translate AI investment into durable cash flow, operational resilience, and long-term value creation.”
Why this matters for private equity investors
According to the report, AI is reshaping several core dimensions of SaaS investing:
- Exit readiness and hold periods: Exit readiness is now a continuous discipline, with median holding periods remaining elevated at approximately five years as longer value-creation cycles and AI integration complexity push sponsors toward extended holds or alternative liquidity strategies.
- AI risk and execution: While AI is inflating deal sizes, rising dependency on foundational providers and recent workforce reductions highlight the need for disciplined execution, realistic margin expectations, and stronger governance as AI scales.
- Operating models: Portfolio companies are reallocating spend toward AI infrastructure, data maturity, and cybersecurity, changing margin profiles and near-term profitability assumptions.
- Exit planning: AI-driven transformation is lengthening value-creation timelines, complicating exit forecasting and increasing the importance of flexible liquidity strategies.
- Governance and talent: As AI capabilities scale, boards and sponsors face heightened demands around governance, technical oversight, and access to specialized talent.
- Risk management: Elevated valuations and uneven early returns from AI initiatives require more rigorous downside protection and scenario planning.
Looking ahead into the remainder of 2026, the report concludes that private equity momentum in software remains resilient, but increasingly dependent on execution. Firms that pair disciplined capital deployment with realistic AI integration strategies are best positioned to navigate longer holding periods, evolving exit pathways, and heightened scrutiny around returns.
For more insights, download the full report today.
