Governance

You’ve done the work. AI is now an effective part of how your organization operates. As adoption expands and new needs emerge, small inconsistencies and risks can surface. Governance is how you keep things steady without slowing them down.

In practice, this means putting simple structures in place. Clear guidelines for when and how AI is used as new use cases emerge. Defined points of responsibility for reviewing outputs and making decisions. Lightweight documentation that makes processes visible and repeatable. Just enough policy and structure to ensure consistency and accountability.

Governance also means staying close to how things evolve and making intentional adjustments based on shared understanding. The goal is not control for its own sake, but ensuring clarity on AI’s role and the need for human judgment.

Over time, this creates a system that’s both stable and adaptable, responsive to change without losing coherence or introducing unneeded complexity. From here, the focus shifts to right-sized training to support people in using these systems well.