AI for private equity

Almost every PE leader is doing something with AI. Almost none would bet on passing an outside audit in ninety days.

You bought the tools. Nothing changed. What was missing is the workflow, built inside the systems you already run.

Book 30 minutesHow an engagement runs
99%
of private equity leaders are exploring, piloting, scaling or embedding autonomous AI
9%
are very confident they could pass an independent AI governance audit within 90 days

Grant Thornton, 2026 AI Impact Survey. 100 private equity fund leaders, February to March 2026.

Vendors will sell you agents. What you are missing is the workflow they run inside: a named owner, a baseline number, a rule for what the machine may touch. That is not a technology problem.

Waiting is not neutral either. It is another year of seats nobody audits, a close that still waits on one person, and the number you own moving the wrong way while the pilot stays a pilot.

Agents are not a workflow. A workflow is not a second brain.

Agents

Most companies I talk to have them: a ChatGPT seat, a "board of advisors" prompt, a bot in Teams.

A workflow

Few companies have one: a named owner, a baseline, a rule for what the machine may touch.

A second brain

Almost no company has one: the one place your rules, exceptions and decisions are written down and cross-referenced, that every agent reads from. Your controller retires. The reason that accrual is booked that way does not retire with them.

The same act, before AI was the tool

Retail finance, 2020Samsung US retail operations

Head of finance, planning, procurement and logistics: $150M budget, close to 30,000 doors, 700 FTEs, a direct team of nearly 20. Answered for the numbers to the CFO every month.

Advisory, 2021A wireless handset wholesaler, advised at CEO level

A product line at 20% gross margin was losing money on every unit. Nothing was built. The range widened and the line turned.This is what the Diagnostic sells

AI implementation, 2026A PE-backed multi-site operator

Four weeks, two site visits, seven deliverables. The biggest item on their automation list was an ERP feature they already paid for, switched off.

How an engagement runs

Three steps. The first can end with "do not build yet."

Step one

The Operator's Diagnostic

Three days inside your team, watching the work. Then a written readout.

  • A process map for each workflow watched
  • Three ranked candidates, each with a baseline and a named owner
  • A verdict: build, fix the data first, or not yet

Fixed fee. The findings are yours to take anywhere, including to someone who is not me.

Step two

Build, with your owner

One or two days a week, with the person who will run it.

  • A knowledge foundation you own
  • Six acceptance tests, written first
  • Shadow mode until the output earns promotion
Step three

Run, measured

Priced per agent in production, not per hour of me.

  • A weekly ledger of hours returned against your baseline
  • The next agent only when the first is used

Thirty minutes. You get my read before you decide anything.

Where AI is landing inside finance and operations teams like yours, where it is not, and what that means for the number you own. Bring the workflow that annoys you most. You will leave with a different set of questions for your team, and those are yours whether or not you ever hire me. Whether we work together is a separate question, and if the answer is no I will say so.

Book 30 minutesguennael@celxadvisory.com