Private Equity
AI Benchmarks

Our first full benchmark with the New York PE community, run ahead of the AI Strategy Day. Adoption has moved faster here than anywhere we measure, but the harder question is the same one facing every market: has that adoption become a durable advantage yet?

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• 89% of firms are integrating AI or beyond, up from 57% in May. Not one firm is still just exploring, and almost no one feels they are genuinely leading the market

• 86% expect their portfolios to scale AI within 12 months, yet only 21% see a durable, measurable advantage in their portfolios today. Near-universal ambition, rare advantage

• Just 34% rate their own firm’s AI use as an established or durable advantage. Adoption is now table stakes; proving the edge is the next chapter

• 82% say what stalls AI in portfolios is people, conviction, clarity, capability and culture, versus just 8% pointing to data or technology

Our third benchmark, and firms have climbed the maturity curve fast, and agentic AI has moved from "is it real?" to "how do we deploy it."

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• 64% of firms are now integrating AI or beyond, up from 42% in March and nearly double last September. Piloting has fallen to 27%

• 79% expect their portfolio companies to scale AI within 12 months, yet only 40% trust their own data foundations. 

• 75% now see agentic AI as balanced or real, up from 52% in March. Scepticism has roughly halved in a single quarter

• People and change is the biggest mobilisation gap, and it is far larger across portfolios (49%) than inside firms (30%). 

Our second benchmark, designed as a shorter pulse to track movement since September 2025. New questions on readiness sentiment, agentic AI expectations, and practitioner tool adoption.

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• Firms at the integrating stage rose from 20% to 31% - the biggest shift since the first benchmark

• Only 27% agree their data foundations are good enough for scaled AI adoption

• 48% say agentic AI is currently more hype than real, yet 75% expect portfolios to scale AI within 12 months

• Barriers to agentic AI are distributed: governance (22%), integration (19%), talent (19%), and data (17%) clustered tightly together

The first AI Pathfinder benchmark, covering ten core areas: AI maturity, governance, data readiness, current applications, barriers, outcomes, capabilities, portfolio support, 12-month priorities, and peer perception.

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• Early-stage adoption dominates: two-thirds of firms are still exploring or piloting AI; only 13% have scaled or reached strategic integration.

• Governance is ahead of maturity: two-thirds of firms report formal AI governance, often led by senior leadership or a dedicated AI team.

• Data readiness is the primary brake: more than 80% rate their data as only adequate or worse.

• Current value remains tactical: efficiency and faster decision-making dominate, while EBITDA uplift and portfolio-wide value are rare.

• The next 12 months: firms are prioritising due diligence, sourcing, and operational efficiency; value creation is secondary.

Our fourth benchmark, and our largest yet. Adoption is now table stakes: the community has climbed the curve, but the harder question, whether that adoption has become a durable advantage.

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• 71% of firms are integrating AI or beyond, up from 33% a year ago. Adoption has climbed so fast it is no longer what sets a firm apart

• 83% expect portfolios to scale AI within 12 months, yet only 40% trust their data foundations and half can articulate a credible ROI case

• Just 18% rate their AI use as an established or durable, measurable advantage. Firms have adopted, but few can yet prove the edge

• 57% say what stalls AI in portfolios is people, clarity, capability, conviction and culture, versus 27% pointing to data or technology

Our first benchmark with the New York PE community, fielded ahead of our inaugural AI Strategy Breakfast Briefing. It establishes the NYC baseline and, notably, lands on the same headline finding as London: the hardest part of scaling AI is people, not technology.

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• 57% of firms describe themselves as integrating AI or beyond, with 11% already calling it strategic. Portfolios are more uneven: 26% report wide variation across their portcos

• 75% expect portfolio companies to scale AI beyond pilots within 12 months, yet only 39% feel their data foundations are good enough. Data foundations are the lowest readiness score by some margin

• 55% now see agentic AI as balanced between hype and reality, not predominantly hype, and 67% expect meaningful, repeatable impact within 12 months

• Change adoption is the number one barrier to scaling agentic AI, named ahead of governance, talent, integration and data. The harder problem is human and organizational, not technical

A sentiment snapshot on Private Equity and Agentic AI

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• Ambition is ahead of readiness

• Agentic AI: belief in value, anxiety about deployment

• Talent & leadership are the swing factors