AI governance monitoring: how to prove your program is actually working
Ask a governance lead which of their AI controls actually ran last Tuesday at 2:14 p.m., when a specific agent touched a specific dataset, and the answer usually arrives as a policy document, an org chart, and a shrug. That gap between the controls a program claims to have and the controls that actually fired when an agent acted is where AI governance quietly fails. Policy documents describe intent. Model monitoring tracks accuracy and drift.