The Industry Funding AI Is Still Figuring Out How to Use It
Private equity firms collectively manage trillions in assets and have written billions into AI companies over the past three years. FTI Consulting's 2026 Private Equity AI Radar, covering 200 fund and operating leaders, shows how those same firms are using AI internally, and the picture is less advanced than the investment thesis might suggest.
The Numbers
36% use AI day-to-day. Across 555 senior PE leaders surveyed globally, 66% report benefits within 12 months. The direction of travel is clear but the penetration is not. 19% of high performers exceeded their business case. High performers are using AI more deliberately than their peers, embedding it into core value creation levers rather than running parallel experiments that never reach production, without necessarily adopting at materially higher rates. The adoption gap and the performance gap are two different problems, and only one of them is closing.
Where PE Firms Are Actually Using AI
Deloitte found 86%, and 84% of US firms have appointed a Chief AI Officer. The use cases break down as follows: 40% applying AI to strategy and market assessment, 35% to target identification, 35% to due diligence. The pattern is consistent with where AI delivers well-defined tasks with structured inputs: screening large datasets of potential targets, summarising industry research, generating first-draft investment memos.
The harder gap is governance: 78% of PE leaders, according to Grant Thornton. Firms have moved fast enough to deploy tools but not fast enough to build the governance around them, and the firms that move ahead of regulators, LPs, and compliance teams now are building an advantage that is hard to replicate.
The Contradiction at the Centre
88% of PE firms, with two-thirds expecting to allocate over a quarter of their budget to AI in 2026, according to Deloitte. Those firms are simultaneously deploying hundreds of millions into AI portfolio companies. The disconnect between how quickly they are moving as investors and how slowly they are moving as operators is real, because investing in AI requires conviction about the market; using AI requires conviction about specific tools, workflows, and governance structures inside a specific firm.
Two statistics look contradictory until you read their scope carefully. About 95% of PE AI initiatives meet their business case, according to FTI Consulting's survey of deliberate, funded programmes. About 95% of broad enterprise generative AI pilots show no measurable return, according to MIT Project NANDA. Both are true, and the difference is selection: the firms that designed an explicit business case, funded it properly, and measured it against clear criteria did fine. The firms that handed out ChatGPT licences and waited did not.
What the Performance Tier Shows
FTI identified a subset of firms, the PE AI Alpha Tier, delivering consistent outsized ROI across revenue growth and cost savings in their portfolio companies, with accelerated time to value and better exit outcomes. They apply AI into core value creation levers rather than treating it as a standalone initiative, measure time-to-value explicitly, and embed AI into the deal process from diligence through exit preparation rather than adding it as an afterthought at each stage.
63% achieve measurable impact within 12 months, and the distribution is widening faster than the average is improving, the pattern you see when a technology creates genuine leverage for firms that integrate it properly and noise for those that do not.
For wholesale investors evaluating PE managers, the AI adoption data is now a legitimate part of the assessment. A fund that cannot answer what AI does for its sourcing, diligence, and portfolio operations is running the same process it ran in 2022 in a market that has changed significantly.
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