AI Moves Into PE's Products

Hi, I’m Lily. I created this PE edition of the AI Dispatch for our growing community of thousands of private equity leaders and portfolio company operators navigating AI implementation.

This week’s theme: Markets reward AI that changes what a company sells, not how it operates.

Faster back offices and automated workflows are quickly becoming the baseline that buyers, LPs, and customers simply expect. The real returns are landing at companies that put AI into the product itself. This week's stories trace that dividing line through fresh valuation data, one of the year's biggest fund closes, and a portco that turned its oldest asset into its newest offering.

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What GPs Are Whispering About

McKinsey Maps the AI Ladder to 31x Multiples

McKinsey's analysis of 471 PE-backed companies delivers a blunt verdict: productivity AI doesn't move valuations. Companies using AI only for efficiency trade at 13x to 14x revenue, nearly identical multiples. The premium starts when AI enters the product itself. Level-three companies trade at 20x, and those building new AI-driven businesses reach 31x, with revenue per employee jumping 52% to $180,000. One PE-owned industrial supplier's AI sales agent re-engaged 30% of inactive customers. For operating partners, the message is to stop counting automated tasks and start asking what AI lets the portco sell. Read more →

Clearlake Raises $14.8B on an AI Transformation Thesis

Clearlake Capital closed Fund VIII at $14.8 billion, one of 2026’s largest raises, built explicitly around AI-driven transformation. Nearly 300 LPs across 35 countries backed the thesis. The engine is Clearlake AI Labs, which embeds with portfolio company management teams to deploy AI across operations, product, and customer engagement. New investments Dun & Bradstreet, Qualus, and ModMed were selected for their AI transformation potential. For portco operators, the signal: sponsors are now raising capital on the promise of AI execution, rather than mere AI exposure. Read more →

Kirkland Taps Palantir to Build AI for PE Fundraising

Kirkland & Ellis, the law firm behind fundraises for Blackstone, Thoma Bravo, and EQT, struck a multiyear deal with Palantir to build AI for private equity fund formation. The tool drafts side letters, tracks LP agreements, monitors compliance, and supports continuation vehicles, putting senior partner judgment in the hands of over a thousand lawyers. It's part of Kirkland's $500 million AI platform investment, the largest disclosed in the legal industry. The firm advised on nearly $500 billion in fundraising targets last year. For GPs, the machinery around fund formation is being rebuilt with AI, and fee structures may follow. Read more →

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Portfolio Gold

Every week, we’ll bring you a new, real-world example of how targeted AI deployments within portfolios are solving persistent business challenges.

Clearlake Portco Dun & Bradstreet Cuts Compliance Time 96% with Agentic AI

Company: Dun & Bradstreet (Clearlake Capital), the 185-year-old business decisioning data and analytics provider, taken private by Clearlake in a $7.7 billion transaction completed in August 2025.

Problem: Compliance teams at D&B’s enterprise customers were at a breaking point. Onboarding, screening, and third-party due diligence workflows took days per case, and the standard response of layering on fragmented software, data, and services wasn’t keeping pace with accelerating regulation and increasingly sophisticated bad actors. Compliance talent has also never been harder to find, leaving teams stretched across manual review work.

Solution: D&B introduced agentic AI capabilities that act inside compliance workflows rather than alongside them. The offering is available within the D&B Risk Analytics platform and, through a Model Context Protocol (MCP) server, lets organizations embed verified D&B data, models, and workflows directly into their own AI assistants and custom agents. The agents automate onboarding, screening, and due diligence, anchored by the D&B Commercial Graph so AI operates on verified, continuously refreshed business identity data rather than unvalidated inputs.

Early Results:

• Up to 20x increase in review capacity

• 70 - 96% reduction in processing time

• 50 - 90% reduction in false positives

• Up to 700% faster resolution of false positives

• KYB onboarding and beneficial ownership determination completed in seconds, delivered into client workflows without human intervention

Less than a year after Clearlake took D&B private on a data-to-AI thesis, the portco is converting its proprietary data moat into agentic products. It’s a clean example of the level this week's McKinsey piece describes: AI embedded in what the company sells, not just how it operates.

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Lily’s Recommendation Corner

Inside private equity’s AI-led transformation with Kyle Roemer

In this episode of Private Equity FunCast, Kyle Roemer, Head of Data & AI at Accordion, breaks down what AI is doing inside middle-market portfolio companies right now. With visibility across Accordion's 350+ private equity clients and real spending data from Ramp, Roemer separates genuine adoption from wishful thinking, walking through the changes function by function so operators can gauge whether they're ahead or behind. His boldest call: the Office of the CFO will undergo the biggest revolution of the next year. A grounded reality check for any portco leader planning their next AI move. Listen here →

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Lily’s Closing Thoughts

Every story this week lands on the same dividing line. McKinsey’s data shows valuations sit still while AI stays in operations, then climb steeply once it enters the product. Clearlake raised $14.8 billion from LPs who are backing execution on exactly that thesis. And Dun & Bradstreet proves it can be done fast: less than a year under Clearlake’s ownership, a 185-year-old data business is now selling agentic compliance products built on its proprietary moat.

But look closer at how D&B got there. The product didn't come out of nowhere; it came from operational capability the company had already built into its data and workflows. That's the real lesson: operational AI and product AI aren't competing strategies; they're a sequence. The portcos deploying AI deep in their operations today are the ones accumulating the data, the workflows, and the institutional muscle to productize tomorrow. The question for your next board meeting isn't whether to start with operations or product. It's whether your operational AI is building toward something a customer will eventually pay for.