Start With Ownership
Leaders need to define who owns AI decisions before tools spread across teams. Ownership includes approving use cases, setting acceptable risk, reviewing data conditions and deciding when human oversight is required.
Make Controls Practical
Useful AI controls are visible in daily work. They show up in intake questions, approval checkpoints, model and vendor records, data restrictions, monitoring routines and escalation paths when outcomes are uncertain.
Treat Literacy As Governance
AI literacy is part of risk management. Teams need enough understanding to recognize weak outputs, protect sensitive information and explain when a decision should stay with a person.