Legal commentary argues AI-assisted internal investigations earn greater regulator credit when built on transparent, statistically validated methodologies

A substantive legal commentary piece published in the New York Law Journal argues that companies deploying AI-assisted document review in internal investigations are more likely to have their investigations credited by regulators where the methodology is transparent and statistically validated — not merely because AI was used. The authors — Sidhardha Kamaraju, David Abramowicz, and Daniel Pohlman — frame the analysis around the insight that regulators apply old evidentiary tests to new technologies: the question is not whether AI was the tool, but whether the process it supported would satisfy the standards regulators have traditionally required of credible internal investigations. This is a significant practical guidance point for in-house legal teams and outside counsel designing AI-assisted review workflows: the legal risk lies not in using AI, but in deploying it without the kind of auditability and statistical validation that regulators expect from any document review methodology. The analysis has direct relevance for UK-based legal teams: the Serious Fraud Office (SFO), FCA, and CMA all conduct investigations in which the quality of a company's internal investigation — and the credibility of the document review underlying it — can affect enforcement outcomes and penalty calculations. As AI document review tools become standard across Magic Circle and US firms operating in London, establishing defensible methodological standards will become a core competency for disputes and investigations groups.