The AI Reckoning in Private Equity
The seismic shift generated by generative AI has reached the valuation models and exit timelines of the enterprise SaaS market. In previous issues of Capital Intelligence, we've explored how organizations fall into the "Waiting for Godot" trap, endlessly delaying AI implementation, and how talent decisions must now prioritize AI-first capabilities. Today, we examine the stark reality: for PE firms, the waiting period is over.
For private equity professionals, this is not merely a technology trend to track; it is an existential filter for investment decisions across all sectors - starting with enterprise SaaS, then rapidly expanding to business services, logistics, and consumer goods. The old, predictable playbook for value creation and exits has shifted, forcing PE firms to weigh a new dimension of strategic risk: is a target company genuinely integrating AI for defensibility and value creation, or is it merely performative?
The Broken Exit Path: A New SaaS Investment Calculus
The formula that fueled a decade of predictable returns in software deals—build to $20M–$50M ARR, maintain decent growth, and wait for the PE check—has been invalidated. The capital flows and buyer mandates have fundamentally changed, creating a "no-man's land" for hundreds of otherwise healthy SaaS businesses.
📊 The New Normal in PE Tech Deals in 2025
58% of VC funding → AI companies (up from <10% in 2022)
24.8% decline in SaaS M&A deal value
15x EBITDA = new baseline (down from 25x peaks)
$400M+ ARR required for IPO consideration
40%+ EBITDA margins = new PE bar for acquisitions
Capital and Buyer Selectivity
VC has moved on: In H1 2025, 58% of global VC funding (64% in the US) flowed into AI companies. This capital drain has resulted in a collapse of mega-rounds for traditional SaaS, drying up the primary source of follow-on funding and valuation support.
PE is brutally selective: M&A deal value in enterprise SaaS dropped 24.8% in Q1 2025, despite activity remaining high. The remaining PE players are setting a very high bar. As firms like Thoma Bravo attest, they are only buying category leaders that demonstrate clear AI integration and a path to 40%+ EBITDA.
Multiples have reset hard: The days of 25x EBITDA multiples for high-growth software are gone. The market has stabilized around a more rational 15x EBITDA, demanding real operational improvement and clear paths to profitability, not just ARR growth.
Strategic acquirers are likewise laser-focused, with corporate M&A now dictated by the mandate to acquire AI capabilities. For the IPO market, the bar is stratospheric, requiring companies to exceed $400M ARR and maintain 30-50%+ growth to even be considered. The middle-tier of the SaaS market is now trapped, lacking both the AI moat for a strategic exit and the scale for a public offering.
The Diligence Imperative: Strategic vs. Performative AI
The core question in a SaaS deal is no longer if a company is using AI, but how deeply and how defensively. PE must differentiate between a company that has strategically integrated AI into its core intellectual property and value proposition, and one that has merely bolted on a low-value chatbot or surface-level feature.
This matrix provides the essential framework for every SaaS deal evaluation. At NextAccess, we've used this exact approach with fund clients to identify which targets have genuine AI moats versus those facing imminent disruption. The differences become stark when you ask the right questions:
If a target cannot prove that its AI strategy creates a genuine, proprietary data or workflow moat, PE must assume an existential risk - that a smaller, more agile pure-play AI competitor will obsolete the current product category within two to three years.
This Isn't Just About SaaS - Every Vertical Faces Risk
While the impact on SaaS is immediate and dramatic, PE professionals should understand that this transition is a mere harbinger for all industries. AI is not a vertical threat; it is a horizontal competitive force that will play out across every segment of the economy.
For any acquisition, in any sector—manufacturing, healthcare services, logistics, or consumer goods—due diligence must now encompass two core elements:
Competitive Risks Created by AI: Assess the risk of disruption from an AI-first competitor. For example, in a logistics company, could a startup using computer vision and machine learning for route optimization and warehouse management render the target's existing operations and software obsolete?
AI-Driven Value Creation Plans: Identify the concrete levers for using AI to drive exponential value creation post-acquisition. This means integrating AI into the operations to achieve previously unattainable efficiency gains and margin expansion. The new value creation playbook must be AI-first.
This is where many PE firms struggle: they understand the threat intellectually but lack the operational expertise to implement AI-driven transformations across diverse portfolio companies. You can't simply hire an AI Operating Partner and expect them to drive AI adoption across a diverse portfolio of companies. You need a systematic, yet tailored, approach to upskill and transform each portco, while taking stock of their industry, culture, and workforce.
Remember our discussion on AI-first talent decisions? The same principle applies across your entire value creation strategy. The firms winning today aren't just evaluating AI defensibility during due diligence - they're actively building AI capabilities post-acquisition through:
Rapid AI capability assessments within the first 100 days of ownership
Cross-portfolio AI implementation playbooks that adapt proven approaches across similar business models
Operational partnerships with firms like NextAccess that have pattern recognition across multiple AI transformations
Achieving exit multiple expansion increasingly comes down to demonstrable AI integration that a strategic acquirer will pay a premium for.
The firms that succeed in the next decade will be those that view their portfolio companies not just as standalone businesses, but as platforms ripe for AI-driven transformation. This strategic vision, coupled with the capital and expertise required to build proprietary AI capabilities, is the only way to generate outsized returns in the coming market cycle.
The NextAccess Advantage: From Due Diligence to Value Creation
The bar is much higher, but the opportunity for firms who adapt is massive. The challenge is execution - understanding AI strategy is different from implementing it across a portfolio.
At NextAccess, we've built our practice on helping PE firms navigate both sides of this transition:
During Due Diligence: We assess targets for genuine AI defensibility versus performative AI, using the frameworks outlined above to identify existential risks before you write the check.
Post-Acquisition: We implement AI-driven transformations that generate the margin expansion and competitive moats that command premium exit multiples.
Whether you're evaluating a target’s AI adoption claims, need to transform a portco’s operations with AI, or want to build systematic AI capabilities within your fund, we bring the operational expertise and pattern recognition that turns AI from a risk factor into alpha.
We're not consultants who study your business - we're operators who've built high-performing organizations and delivered exceptional results for investors.
Want to discuss how AI is reshaping your specific investment thesis or portfolio strategy?
Message Scott Kosch or Valerie VanDerzee to schedule a complimentary 30-minute consultation to explore how our expertise can help your organization.
NextAccess Authors: Scott Kosch and Valerie VanDerzee
NextAccess is an advisory firm of experienced operators with deep experience running top-performing organizations and delivering exceptional results. We help executive teams and investors build stronger, more valuable companies through a powerful mix of operational expertise, strategic insight, and data-driven solutions.