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What risks does AI DD uncover?

The most common findings fall into five categories.

AI capabilities that exist only as demos, not production systems. Data quality gaps that undermine AI accuracy the moment you scale. Model bias that creates regulatory exposure your legal team hasn't priced in. Teams that built the system but cannot maintain it post-close, especially after key engineers leave during the transition. And technical debt that doubles your expected integration costs.

In our experience, the gap between what CIMs claim about AI and what actually exists in production is where deal value gets destroyed. The DD exists to close that gap before you close the deal.

See our full AI due diligence service →

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