Is Your AI Governance Actually in Place, or Just Written Down?

AI Governance Checklist

Free PDF Updated The Jonesi Consultancy
Governance Checklist Self-Audit For Leadership Checklist
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About this resource

What this guide covers

A policy can be complete and governance can still be absent. The distinction is whether the things in the document are true in practice: whether a named person actually owns it, whether staff can state the data rule without looking it up, whether the review point is observed, and whether anybody has ever used the reporting route.

This checklist tests that. It is deliberately written as observable conditions rather than as intentions, so each item can be verified rather than believed. Where the Anatomy of a Practical AI Use Policy audits the document, this audits the reality, and the two frequently disagree. Run it quarterly and the drift becomes visible while it is still small.

Every item is written as something you can check rather than something you can believe. A governance item you cannot verify is an intention.

How to use it

Purpose, and how this will help

Run it quarterly, and score it on what an employee could demonstrate rather than on what the policy says. The single most informative item is whether anyone has used the reporting route: a route nobody has used in a year is not evidence of a flawless organization, it is evidence that people do not believe reporting is safe.

Inside the download

What you'll take away

1

Test for a real owner

Whether a named person owns governance, or whether everyone assumes somebody else does.

2

Check the approved list

Whether it exists, and whether it has changed since it was written.

3

Test staff recall

Whether people can state the data rule without looking it up.

4

Verify the review happened

Whether the review date was observed or quietly passed.

Who this is for

  • Governance owners running a periodic self-audit
  • Internal audit and risk committees
  • Executives asking whether the policy is working
  • Compliance leaders preparing for an external review

Common questions

Frequently asked

How do you know if AI governance is working?

Test observable conditions rather than reading the policy. Can a named person be identified as the owner? Can staff state the data rule without looking it up? Has the approved tool list changed since it was written? Was the review date observed? Has anyone used the reporting route? Governance that passes those is real.

How often should AI governance be reviewed?

A light quarterly check and a substantive annual review. The quarterly pass catches drift while it is small, particularly on the approved tool list and the reporting route. The annual review is where scope, boundaries, and ownership get genuinely reconsidered.

What does it mean if nobody has reported an AI mistake?

Almost never that no mistakes have occurred. It usually means people do not believe reporting is safe, or do not know where to report. Both are governance failures, and both are invisible until an unreported mistake becomes an incident.

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