The Governance Conversation Nobody Wants To Have

Every time I bring up AI governance in a room full of audit leaders, I get the same reaction. Eyes glaze over. People shift in their seats. Someone checks their phone.

I get it. Governance sounds like bureaucracy—something that slows things down, creates committees, and produces unread policy documents. Honestly, in many organizations, that's exactly what it has become.

But here is the thing — bad governance is not the only alternative to no governance. And in the context of AI, the absence of governance is not freedom. It is a liability you have not priced yet.

When a business unit secretly deploys an AI tool, that's not innovation—it's shadow risk. When AI produces results no one can explain or trace, that's not efficiency—it's an audit finding waiting to happen. And when the audit committee asks how AI is used, and no one has an answer, that's a credibility problem—on your desk.

Good AI governance does not have to be complicated. At its core, it answers three questions:

1.      What tools are we using?

2.      Who is accountable for the outcomes they produce?

3.      And how do we know when something has gone wrong?

Those three questions, answered clearly and documented simply, protect your organization and protect your function. They also happen to be the foundation for scaling AI responsibly — which is the only way scaling actually sticks.

Audit functions are well-placed to lead this conversation. You may not formally govern AI, but you understand risk, accountability, and effective controls. These skills are what your organization needs now and likely lacks elsewhere.

The audit functions that step into this space early are not just managing risk. They are earning a seat at a table that will define how their organization operates for the next decade.

That opportunity is available right now. Will you take it?