Capital Resources
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Acquisition Target AI Due Diligence Checklist
A buyer's field guide to AI due diligence: how AI targets differ, what to probe in the data and model layers, the red flags that kill deals, and a full diligence checklist.
Buying an AI company is not like buying a normal software business. The asset you think you're paying for — the model, the data, the team — is often more fragile, more entangled, and more expensive to keep running than the demo suggests. This guide is a buyer's field manual: how AI targets differ, what to probe in the data and model layers, the red flags that should pause a deal, and a complete diligence checklist you can run with your advisors.
What's inside
- 01Why AI diligence is different
- 02The data layer: rights, provenance and leakage
- 03The model layer: what's real versus narrated
- 04Engineering, infrastructure and unit economics
- 05Talent and key-person risk
- 06Legal, IP and regulatory
- 07Commercial quality and the moat
- 08The diligence checklist
Includes 3 cited references and worked examples, written in plain language you can act on.
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