AI governance becomes difficult when it stays abstract. Teams agree that AI needs oversight, but then face practical questions: Who owns the model inventory? What evidence should be retained? How do auditors test a system that changes over time? What counts as acceptable risk? For internal audit, risk, and compliance teams, the work is not to slow AI adoption. The work is to make AI use traceable, tested, and defensible. That means building a governance program that covers the full life...