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AI Inventory & Governance
Whether the target can show what AI is in use, who owns it, and how AI decisions get made.
Key diligence question
Show the current AI inventory and name the person who can defend it.
AI Due Diligence Diagnostic
Leap's 12-question diagnostic helps PE deal teams identify whether AI claims, controls, model dependencies, or value-creation assumptions need a focused diligence workstream.
The Premise
Use the screen when a target markets AI capability, uses AI in sensitive workflows, depends on model vendors, or includes AI upside in the value-creation case.
AI is in the growth story. The target markets AI capability, embeds AI in products, or uses AI to support differentiation.
AI touches sensitive workflows. AI is used in customer data, pricing, underwriting, claims, compliance, hiring, or finance processes.
Model dependency matters. Key workflows rely on a model provider, AI platform, or vendor terms that may affect cost, access, or liability.
AI upside is in the value-creation case. AI savings, revenue lift, or productivity gains are part of the underwriting case or post-close plan.
What We Evaluate
We publish the domains and the signal we look for. The detailed evidence requests, interview guide, and diligence workplan stay inside the advisory workstream.
Whether the target can show what AI is in use, who owns it, and how AI decisions get made.
Show the current AI inventory and name the person who can defend it.
Whether sensitive data exposure is controlled and employee AI usage is visible enough to assess.
If a deal team asked where confidential data entered public AI tools, could the target answer?
Whether external AI claims hold up against operating reality and whether AI-specific obligations are scoped.
Compare the sales deck AI claim to the technical evidence. What is substantiated?
Whether the AI capability is defensible and whether the architecture leaves credible provider optionality.
What is left of the AI value proposition if the model vendor changes pricing or product access?
Whether high-stakes AI output is validated and whether failure modes have been mapped to deal protections.
Which AI failure would create a valuation, insurance, or RWI issue first?
Whether AI upside is sized, owned, and feasible under the target's operating constraints.
Which AI use cases are real enough to underwrite, and who owns post-close execution?
Run The Screen
Answer twelve questions based on the diligence evidence available today. Unknown is a valid answer, and it is scored as risk. Your detailed answers stay in this browser.
Include public generative AI tools, internal models, embedded vendor AI, APIs, and automated workflows.
Unknown is valid, and scored as risk
How It Is Used
The public screen is a directional triage. The paid work packages the evidence review, management challenge, AI risk heatmap, value-creation pressure test, and deal-team readout behind the score.
Use the twelve questions to identify whether AI risk or upside deserves a discrete workstream before IC.
Run a focused session with the deal team to pressure-test evidence, unknowns, and management claims.
Validate the target's AI inventory, controls, claims, model dependencies, failure modes, and value creation case.
Get In Touch
Bring a live target, data room evidence, and the open questions your deal team cannot yet defend. Leap will help decide whether AI risk, AI claims, or AI value creation deserve a focused workstream before close.