•Transactions•8 min read
The AI Due Diligence Checklist Investors Actually Use
What investors now demand in AI-heavy deals—from dataset provenance to governance cadences—and how to prepare.
Investors now open data rooms expecting a clear view of AI risk. This is the checklist we use when running sell-side and buy-side diligence.
Foundational Questions
- Do you know every AI-enabled workflow in the business?
- Can you explain dataset provenance and licensing terms?
- Are there policies for prompt usage, fine-tuning, and model retirement?
Documentation Package
- Model inventory with risk ratings and control owners.
- Security assessments covering cloud posture, vendor risk, and incident response.
- Regulatory filings, correspondence, and remediation plans.
- Lex LLM governance artefacts demonstrating evaluation and human oversight.
Commercial Impact
Buyers will discount valuations when they see untracked models, ambiguous IP ownership, or gaps in governance. Sellers who show disciplined controls often negotiate stronger terms and faster closings.
Diligence is no longer an IT exercise. It is a trust exercise—prove that your AI estate is safe, compliant, and commercially defensible.