AI Due Diligence for Private Equity
A board-ready operating review of how AI changes the investment case. Built for deal teams underwriting targets whose economics are increasingly shaped by AI-enabled competitors.
What AI changes in diligence
AI changes the investment case for ordinary businesses, not just AI-native ones. A target can look operationally healthy today and still be vulnerable to better-run AI-enabled competitors. It can have strong AI upside and lack the management discipline to capture it. Pricing pressure can move before the numbers reflect it.
The relevant diligence questions are no longer only what systems do they use? They are how exposed is the target to AI-driven change, where is the real upside, and can management and the operating model capture it.
That is the question this review answers.
What we review
Sector AI relevance and disruption pressure
Where the target's market is being reshaped by AI-enabled entrants, pricing pressure, or substitution risk — before management has felt it in the numbers.
Current operating-model baseline
How the business actually runs today: where margin is made, which workflows carry the cost, and which depend on tacit human judgement that AI changes.
Workflow-level opportunity mapping
The specific workflows where AI shifts unit economics — proposal drafting, case prep, underwriting, client servicing, internal reporting — sized by hours, error rate, and revenue exposure.
Systems, data, and API enablement
Whether the stack and data structure can support implementation, or whether the target needs upstream remediation before AI workflows can be deployed reliably.
Management and change readiness
Whether the leadership team has the briefing, delegation, and review discipline AI workflows require — not whether they have an AI strategy slide.
Legal and governance friction
Contractual constraints, regulatory exposure, IP and confidentiality issues that determine which AI workflows the business is actually free to deploy.
Phased post-close value-creation priorities
A sequenced 12–24 month plan the operating partner can hand to incoming management on day one — what to fix first, what to compound on, what to leave alone.
What the report looks like
A board-ready document the investment committee can act on, not a slide pack about tools.
- 01
Executive scorecard against AI vulnerability, upside, and execution readiness.
- 02
Disruption exposure summary — sector-specific pressures and competitor positioning.
- 03
Workflow economics findings — the workflows that matter, sized in hours and margin.
- 04
Systems and data readiness — what the stack supports today and what it doesn't.
- 05
Management readiness — briefing, delegation, and review discipline assessment.
- 06
Legal and governance friction — deployable surface versus contractually constrained surface.
- 07
Pre-close recommendations — what to flag to the IC, what to price in, what to make conditional.
- 08
Post-close priorities — sequenced 12–24 month value-creation plan.
Where this sits alongside legal, commercial, and tech DD
This is not a replacement for legal, commercial, cyber, or technology diligence. It is an operating review that helps the deal team understand how AI changes the investment case and what management should do after close.
The work runs alongside the other workstreams and feeds into them: clarifying which legal or technical questions the deeper streams should pick up, and supplying the workflow economics the commercial team needs to underwrite AI-related upside or erosion.
From diligence finding to value-creation plan
The diligence output is structured so the operating partner can hand it to incoming management on day one. Workflow opportunities are sequenced. Management capability gaps are named. Systems and data work is scoped enough to put into the first 100-day plan.
Findings translate into a phased 12–24 month plan: what to prove out quickly, what to compound on, what to leave alone until the operating model can absorb it. The same Plan, Implement, Review framework that underpins the review underpins the post-close work.
What makes this review different
Built for PE deal teams
Structured to fit deal timelines and IC formats. The output is a document the investment committee can act on, not a generic readiness deck that needs translating.
Relevant to ordinary mid-market targets
Works for professional services, financial services, industrials, and other non-software businesses whose economics are now being reshaped by AI-enabled competitors. Not just AI-native or SaaS targets.
Designed to flow into post-close value creation
The diligence output becomes the operating partner's value-creation plan. Findings don't stop at risk — they translate into a sequenced post-close brief for incoming management.
Have a target on the desk?
Tell us what you're looking at and we'll tell you what this review would cover, how long it would take, and what it would cost.