AI Governance Is Broken Because It’s Not Executable

This article argues that AI governance often fails because it exists as static documentation rather than an operational system. It introduces a model where governance is embedded into delivery pipelines through policy-as-code, automated controls, and continuous validation. By treating governance like software—with inputs, enforcement points, and measurable outputs—organizations can ensure compliance, reduce friction, and scale AI systems safely.