AI Diligence for Private Equity

AI will grow or tank your EBITDA. Stop guessing which.

Every portfolio company is an AI bet — you're just not underwriting it yet. We quantify the technology readiness, financial impact, and execution risk so your IC gets a number, not a narrative.

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The Diligence Gap

Your QofE Doesn't Cover This

Traditional diligence evaluates what the business did. AI diligence evaluates whether that business model still works in 36 months.

What Traditional Diligence Misses

Which service lines are automatable — and on what timeline
Whether the target's technology stack can support AI or will require rip-and-replace
How competitors are already using AI to undercut pricing or win deals
Management's actual AI readiness vs. what they put in the CIM
The real EBITDA impact — up or down — over the hold period

What We Underwrite

Technology readiness: systems, data maturity, integration complexity
Financial impact: quantified EBITDA effect by service line and scenario
Execution risk: management capability, capital required, time to value
Competitive exposure: who's deploying AI and what it means for pricing
Clear deal verdict with conditions your IC can act on

Market Reality

AI Is Repricing Every Deal

72%

of PE firms say AI is a top-3 factor in underwriting, but few have a framework

40-60%

of service revenue sits in bands where AI can automate or commoditize delivery

200-500

basis points of margin improvement from targeted AI implementation post-close

3-8x

EBITDA multiple premium for platforms with demonstrated AI capability

AI is the single largest variable affecting portfolio company value over the next hold period. Sponsors without a structured way to underwrite it are mispricing both downside risk and upside potential.

What We Answer

The Questions Your IC Is Already Asking

We built this framework around the questions that actually change deal outcomes.

What percentage of this company's revenue is vulnerable to AI-driven disruption — and over what timeframe?

Is the technology stack AI-ready, or are we underwriting a rip-and-replace before we see any value?

Where are the highest-confidence AI value creation opportunities, and what capital and timeline do they require?

Are competitors already deploying AI to win deals, compress pricing, or automate delivery?

Can this management team actually execute an AI roadmap, or does the thesis require new capability?

What is the quantified EBITDA impact — positive and negative — of AI over the hold period?

Does the AI thesis support the deal, require conditions, or suggest a pass?

Our Framework

Three Dimensions. One Verdict.

We underwrite AI across the three dimensions that actually determine whether it grows or shrinks EBITDA.

Risk & Readiness

Defensive Assessment

What AI threatens, what's defensible, and how ready the business is to respond.

Revenue-at-risk by service line and automation band
Technology stack & data maturity scoring
Competitive AI adoption and pricing pressure
Management readiness and talent gaps

Value Creation

Offensive Opportunities

Where AI creates margin, accelerates growth, or unlocks new revenue.

Internal automation: back-office, reporting, quoting, close
Delivery enhancement: faster, cheaper, better for customers
New revenue: AI-enabled products and service tiers
GTM acceleration: pipeline, pricing, proposal velocity

Financial Impact

EBITDA Modeling

The dollar answer: what AI actually means for the P&L over the hold period.

Scenario-based EBITDA impact: base, bull, and bear
Capital required and deployment timeline
Revenue-at-risk quantification by service line
Net margin effect after implementation cost

AI Readiness Score

Technology, data, and organizational readiness scored 0-100 with gap analysis

EBITDA Impact Model

Quantified upside and downside by scenario across the hold period

Prioritized Roadmap

Ranked initiatives by confidence, capital required, and time to value

Engagement

Two Phases. Clear Deliverables.

Start with the assessment. If the thesis is strong, we build the proof of concept.

Phase 1

AI Underwriting & Prioritization

We assess the target's AI risk exposure, technology readiness, and value creation potential — then deliver a quantified thesis your IC can act on.

AI Readiness Score: technology, data, and organizational capability
EBITDA impact model: upside and downside by scenario
Revenue-at-risk analysis by service line and automation band
Ranked AI initiatives by confidence, capital, and time to value
Deal verdict with conditions — IC-ready presentation

Answers: "What does AI mean for this deal — and what's it worth?"

Phase 2

Working Prototype

For the highest-priority initiative from Phase 1, we build a working prototype to validate the thesis before you commit post-close capital.

Functional proof of concept for top-ranked AI initiative
Technical architecture and integration roadmap
Build vs. buy vs. partner cost model
Success metrics and 90-day deployment plan
Demo-ready artifact for IC or portfolio leadership

Answers: "Does this actually work, and how fast can we scale it?"

Phase 1 delivered in 5-6 business days. Phase 2 scoped at completion of Phase 1.

Risk Classification

We Quantify the Risk. You Make the Call.

Every engagement produces a clear AI risk classification so your IC knows exactly what they're underwriting.

AI Tailwind

Low disruption risk, high value creation potential. AI is a clear accelerant to the existing thesis.

Manageable Exposure

Material AI variable, but defensible with targeted investment. Quantified conditions and capital requirements included.

Significant Uncertainty

Key assumptions unvalidated. AI impact could swing EBITDA materially in either direction. Phase 2 prototype recommended.

Severe Risk

Core revenue streams face existential automation pressure. Disruption timeline is shorter than the hold period.

Common Questions

Questions from Sponsors

Any business where AI meaningfully changes the economics — services, professional services, healthcare services, government contracting, IT staffing, BPO, field services, and more. If the business relies on labor to deliver, AI is a variable. We size it.

A CIM and a revenue breakdown by service line. If you have management presentations, org charts, or technology documentation, that accelerates things — but we can work from a CIM alone. We supplement with public data, competitive intelligence, and industry benchmarks.

Technology diligence evaluates systems and infrastructure — "is the tech stack sound?" We evaluate how AI changes the economics of the business — revenue at risk, margin expansion potential, competitive positioning, and the dollar cost to execute. We deliver a financial thesis with EBITDA impact, not a tech stack report card.

Yes — that's how it's designed. Phase 1 runs on a 5-6 day timeline in parallel with your existing diligence workstreams. The deliverables are IC-ready and slot directly into your investment memo alongside QofE, commercial, and legal findings.

Then it saved you from a bad deal. The analysis is independent — if AI risk is existential and the value creation levers don't credibly offset it, we'll say so. A "pass" with documented rationale is one of the most valuable deliverables we produce. It protects capital and sharpens your thesis for the next deal.