How to Establish AI Decision Rights Before an Accreditation Review

For many institutions, an accreditation review is the first time an outside body asks how they govern AI. It is often also the moment leadership realizes that what they have is an AI policy, and not much underneath it. A reviewer wants to understand who holds authority over the institution's AI, and a policy does not tell them that.

What accreditors are now asking about AI

Accreditors in both higher education and healthcare are moving toward the same expectation, that leadership can show it governs AI deliberately. They want evidence that someone is accountable for each high-risk system, that human judgment is preserved where it matters, and that the institution can show how its AI decisions are made and overseen. Saying the institution has an AI policy no longer answers that. What a review is really after is authority, and authority has to be documented before anyone can examine it.

What AI decision rights are

AI decision rights are the documented answer to a straightforward question: who has the authority to approve, restrict, override, or stop an AI system, and who is accountable for what it does. A policy can describe how an institution intends to govern AI. Decision rights show who actually governs it, which is what an accreditor can examine. In practice they take shape through a decision authority map that names who holds authority across the institution, the Human Authority Line™ that marks where algorithmic recommendation ends and human judgment must remain, and the override and escalation protocols that make that authority real. Together they form the foundation of a governance architecture calibrated to your institution and to the accreditor you answer to, and the work builds from there.

How to establish them before the review

An accreditation deadline is a useful forcing function. Working back from the review date, the first task is to find where AI is actually in use, including the tools that arrived embedded in systems the institution already had. From there, leadership maps who can approve, restrict, or stop each high-risk use, and who answers for it. The decisions that must stay human are written down, with a named owner. And the whole of it is documented in a form leadership and the board can speak to, since reviewers often put the question to leadership directly. An institution that works this way ends up with the governance it needed regardless, built on the timeline the review provides.

Decision rights you keep

The reason to do this ahead of a review is not the review itself. The decision rights an institution establishes for an accreditor are the same ones it will rely on when a regulator or its own board asks the same question, and they are the institution's to keep. When an institution asks for help establishing AI decision rights before an accreditation review, this is the work behind it, and what the institution walks away owning. See what an engagement produces