Board-Level AI Governance: The Five Decisions Only Executives Can Make
A major insurer's AI system was denying coverage claims. When humans reviewed those decisions, 90% were found to be wrong. The insurer's engineering team had built a performant model. Their MLOps team had solid deployment pipelines. Their data scientists had rigorous evaluation metrics. None of that mattered, because no one at the board level had ever answered the question: what is our acceptable failure rate for AI decisions that affect whether a sick person gets treated?
That gap — between functional technical systems and missing executive decisions — is where AI governance most often breaks down in practice. The result is organizations that are simultaneously running AI in production and exposed to liability they've never formally acknowledged.
