Five AI Governance Gaps That Cause Real Production Incidents, Explained

A practitioner working in AI governance has identified five critical blind spots that most organizations overlook when managing AI systems in production. These include undetected shadow AI deployments, sensitive data leaking through prompts before logs can capture it, and sub-agents gaining capabilities beyond their intended scope. Two additional gaps involve delegated credentials that outlive their authorized timeframe and audit logs that cannot be independently verified by regulators. The author argues that most governance tools focus on individual system components rather than the connections between them, which is where unauthorized AI activity tends to occur.