AI Diligence
The per-deal answer to one question: what will AI do to this business? $15,000 per target at screening stage, $25,000 confirmatory. Runs on deal documents and management sessions, so it works on private targets. IC-ready memo section delivered to your deal timeline.
Every CIM now claims the target "uses AI." Almost none of them answer the questions that move value: which revenue lines could AI agents absorb, whether the data is a moat or a liability, and what the business quietly depends on that a model vendor could reprice next quarter.
Standard diligence does not catch this. Quality of earnings tells you the margins are real today. AI Diligence tells you whether they survive the next five years, and where the upside is hiding if you own the company.
Boundary worth knowing: the Screening Report tells you what is in the public record about a company. AI Diligence tells you what AI will do to the target's business. When a deal also needs public-company context (comps, competitors, acquirers), we bundle a Screening Report at about 10% off.
By Dr. Leigh Coney, Founder of WorkWise Solutions
Four Exposures Standard DD Misses
Model dependency
What the business quietly relies on: third-party models, APIs, and AI-flavored vendor tools whose pricing, terms, or existence can change under you. Concentration risk, but for intelligence.
Data moat
Whether the target's data is actually proprietary, actually usable, and actually a barrier, or a pile of unlabeled exhaust with privacy obligations attached.
Agentic substitution risk
The uncomfortable one: which of the target's revenue lines are services an AI agent could deliver in two years, and what that does to your exit multiple.
AI talent
Who actually built and runs what the CIM calls "our AI," whether they stay through close, and what replacing them costs.
Two Depths, One Structure
Screening-stage ($15,000) runs on the data room and the deal documents: enough to decide whether AI risk changes your interest or your price. Confirmatory ($25,000) adds management sessions and deeper data and contract review: enough to put numbers in the model and conditions in the SPA.
Both end in the same place: an IC-ready memo section with risk scoring, delivered to your deal timeline, and a Q&A with the deal team.
Every engagement includes
- ✓AI vulnerability assessment: model dependency, data moat, agentic substitution risk, AI talent
- ✓AI opportunity map with effort estimates: where AI expands margins if you own the company
- ✓Deal-document review through the AI lens: contracts, vendor agreements, data terms
- ✓IC-ready memo section with risk scoring, delivered to deal timeline
- ✓Deal-team Q&A
Confirmatory adds: management sessions plus deeper data and contract review.
Portfolio-Company AI Assessment
The same structure, pointed at companies you already own, oriented to value creation instead of deal risk. Which functions move first, what it costs, and what it is worth at exit.
One fund, assessments across the portfolio: the operating partner gets a comparable scorecard instead of ten inconsistent vendor decks.
The natural sequence
Assess first, train after. The assessment finds where each company stands; functional workshops run per company move the ones worth moving, with a cross-portfolio adoption scorecard for the sponsor.
One sponsor relationship, many engagements, one consistent methodology across the portfolio.
AI Diligence FAQ
When in the deal should we bring this in?
Screening-stage works best before the LOI, when AI risk can still change your price or your interest. Confirmatory runs alongside the rest of confirmatory diligence and feeds the IC memo and the SPA conditions. Either way, tell us the IC date and we work backward.
The target barely uses AI. Is there anything to diligence?
Usually more, not less. A target with no AI posture still has agentic substitution exposure on its revenue lines and an unexploited opportunity map. "No AI" is a finding with a price attached, in both directions.
How does this differ from technology due diligence?
Tech DD audits the stack: architecture, security, code quality. AI Diligence prices a different question: what AI does to the business model, the moat, and the margins. The two complement each other and often run in parallel.
Is our deal data safe?
Yes. Work runs under NDA on zero-retention architecture: deal documents are processed, never stored, and never train public models.
Can we bundle public-company research?
Yes. When the deal needs comps, competitor, or acquirer context, a Screening Report bundles at about 10% off.
Put It on the Deal Timeline
A 30-minute call: target profile, data-room status, and the IC date. We confirm scope and start date on the call.
Book a Deal-Timeline CallRelated
Screening Report
Deep research on the public companies around your deal: comps, competitors, acquirers. $5,000 per company.
Portfolio Company Training
Assess first, train after: leadership briefings and functional workshops per company, with a cross-portfolio adoption scorecard. Scoped per engagement.
Custom Build
When the opportunity map justifies dedicated software: fixed-scope builds on your stack, from $75,000.