Where should AI governance actually live?

Most organisations now have an AI policy. That is a good start, but a policy is not an operating control. Once AI becomes part of finance, sales, customer service or administration, the safeguards have to work inside the process itself. A document on a shelf cannot enforce a permission.

The first job is translating policy into practical rules. What information can the workflow access? Who can approve an action? What must be recorded? What happens when the system is uncertain? Those answers should shape the integration and workflow design from the very beginning.

Human oversight needs to be specific too. Assign named responsibility for reviewing important outputs and monitoring exceptions, rather than assuming someone will notice. Then test that access restrictions and approval steps behave as intended, including when the workflow receives inputs nobody expected.

At Aventine AI we see governance and useful automation as partners, not opposites. Clear boundaries give a business a dependable basis for deciding where to proceed and where to pause. The objective is measurable improvement, with control retained over information, actions and accountability.