Views on AI as a challenge are closely aligned between investors and management teams, with 18% of GPs and 17% of portfolio companies identifying it as a concern, reinforcing that AI is becoming a shared area of focus in exit preparation. For management teams, the challenge is often practical: fragmented data, unclear ownership of use cases, limited deployment at scale, and difficulty quantifying the impact of AI initiatives can make it harder to present a coherent AI narrative to buyers.
AI is therefore becoming a more important lens through which buyers assess both risk and upside. On the risk side, buyers want to understand whether AI could reshape the target company’s market, including its impact on pricing power, customer behavior, cost structures, service delivery models and barriers to entry. On the upside, they are assessing whether the company has a credible plan to use AI to improve productivity, commercial effectiveness, decision-making, product development or customer experience.
Importantly, buyers are likely to distinguish between AI activity and AI strategy. A list of pilots or isolated productivity tools may not be enough to support valuation. A credible AI strategy should show where AI is embedded in the operating model, how benefits are measured, what governance is in place, and how adoption can scale under the next owner.
This re-emphasizes the importance of data readiness: without clean, accessible and well-governed data, AI claims can quickly become difficult to evidence in diligence. As a result, AI is becoming part of the equity story. Firms are expected to articulate not only how they are using AI today, but how AI affects future value creation, competitive positioning and downside risk. Those that can demonstrate tangible progress, quantified benefits and a credible roadmap are likely to build stronger buyer confidence. Those that cannot may face deeper scrutiny, longer diligence timelines and valuation pressure, particularly in sectors more exposed to AI-led disruption.
Be exit-ready, not exit-reactive.
PE is entering a period where exit execution discipline matters more than ever. Although market conditions often fluctuate due to external factors beyond PE’s control, firms that embed exit planning early—by strengthening data infrastructure, maintaining disciplined reporting, adopting AI and emerging technologies, preparing management thoroughly, and developing a credible, evidence-based equity story — will be best positioned to capitalize on opportunities to convert performance into realized value. The firms that outperform in this environment won’t necessarily always be those with the best-performing assets; they’ll be the ones that are “ready to move” decisively when the market allows.