The AI Execution Gap: What PE Operating Partners Must Solve in 2025
By Scott Still, Managing Partner, Lancor New York
Across the Private Equity ecosystem, AI has moved from experimentation to expectation. Sponsors are underwriting value creation plans that assume meaningful uplift from AI-driven pricing, productivity, and operational efficiency. Yet the majority of portfolio companies are still struggling to convert investment into impact. With **56 percent of AI initiatives failing to deliver expected returns ***, the burden increasingly falls on Operating Partners to close the execution gap and ensure that AI becomes a driver of EBITDA, not a distraction.
Three themes are defining the portfolios that are pulling ahead: commercial discipline, enterprise governance, and leadership capable of scaling transformation.
1. Anchor AI to the Value Creation Plan
Both Investing Professionals and Operating Partners know better than anyone that value creation is a sequencing problem. AI succeeds only when it is tied directly to the underwriting thesis and the operational roadmap. Too many management teams still pursue pilots that are interesting but do not move the needle. This can be innovation theater, and it consumes time, capital, and organizational bandwidth.
The most effective Private Equity firms are now pushing management teams to identify two or three AI use cases that directly influence the P&L. These typically fall into categories such as pricing optimization, demand forecasting, supply chain resilience, or customer churn reduction. The goal is not to explore AI. The goal is to deploy it where it drives real alpha.
This requires executives who can translate AI capabilities into commercial outcomes. Technical fluency matters, but commercial fluency often matters more. The leaders who succeed are those who can prioritize, build cross-functional alignment, and drive measurable results within the first 12 to 18 months of ownership.
2. Build Governance That Protects Enterprise Value
As AI becomes embedded in core workflows, governance is no longer optional. The World Economic Forum’s work on AI sovereignty underscores the need for companies to maintain control over their data, models, and decision frameworks *. For PE-backed companies, this is a direct enterprise value issue.
Operating Partners are increasingly stepping in to help management teams define governance structures that clarify ownership, risk thresholds, and escalation paths. Boards want confidence that AI-driven decisions are transparent, auditable, and aligned with regulatory expectations. They also want assurance that the company is not becoming dependent on opaque third-party models that limit strategic flexibility.
The companies that get this right treat AI governance as a strategic capability. They build cross-functional oversight, ensure model accountability, and create a culture where leaders understand both the power and the limits of AI. This requires executives who can bridge technology, regulation, and business strategy.
3. Solve the Scaling Problem Across the Portfolio
Even when a single company gets AI right, scaling success across a portfolio is a different challenge. The World Economic Forum’s research on circular supply chains highlights a truth that applies equally to AI: scaling transformation requires orchestration, incentives, and leadership alignment. *
Operating Partners are uniquely positioned to drive this. They can identify repeatable patterns across the portfolio, create shared playbooks, and accelerate adoption by connecting management teams that are solving similar problems. They can also ensure that AI initiatives do not stall at the pilot stage by embedding change management, frontline adoption, and cross-functional operating models.
But scaling is ultimately a talent problem. Many traditional operators excel in steady-state environments but struggle in AI-enabled transformations. The next generation of value creation requires leaders who combine commercial acumen, digital fluency, and the ability to mobilize organizations around change.
The Operator Advantage
At Lancor, we see a consistent pattern. AI is not failing because the technology is immature. It is failing because leadership teams are not equipped to translate it into value. Independent Board members who bring an operational mindset and the best Operating Partners are the critical link between investment thesis and execution reality. The firms that win will be those that pair capital with the right leadership and the right operating model to turn AI from aspiration into advantage.
*Sources
- https://scheinerinc.com/why-56-of-ai-investments-fail-the-innovation-theater-problem/
https://www.weforum.org/publications/rethinking-ai-sovereignty/(weforum.org in Bing)https://www.weforum.org/publications/circular-transformation-of-industries-the-art-of-scaling-circular-supply-chains/(weforum.org in Bing)
