AI Is Rewriting Technology Due Diligence Checklists — Most Firms Haven't Noticed

Technology due diligence checklists have historically evolved slowly — cloud migration status, security certifications, and technical debt inventories have been fixtures for years. AI adoption is compressing that evolution into quarters instead of years, and most standard diligence frameworks haven't caught up.

Two questions now belong on every technology diligence checklist that weren't standard eighteen months ago: how much of the target's product or operations depend on AI systems that are difficult to reproduce or govern, and how exposed is the business to the AI infrastructure and licensing costs of its largest vendors as usage scales post-close.

We're also seeing AI change the economics of diligence itself — well-run diligence teams are using AI-assisted code and architecture analysis to cover far more ground in the same engagement window, surfacing findings that would previously have required extending the diligence period. Sponsors evaluating consulting partners should be asking not just what a firm looks for, but how it's using technology to find it faster and more thoroughly.