Key Questions Boards Must Answer Before Approving AI Coding Tool Deployments

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Corporate boards are being urged to demand rigorous evidence before approving AI coding tool rollouts, going beyond vendor productivity claims. A July 2025 METR study found that experienced developers actually took 19% longer on tasks when using AI tools, despite believing they had worked faster. Experts recommend boards request baseline metrics covering defect rates, delivery times, and rework costs, alongside detailed maps of what data and systems the tools can access. Risk frameworks such as the NIST AI Risk Management Framework and Secure Software Development Framework are cited as guidance for structuring board-level oversight. Key warning signs include business cases built solely on vendor statistics and unverified claims that vendor systems do not train on company data.

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