An AI Governance Checklist for Small Business (Free Outline)

AI governance for a small business does not need a committee. It needs a short checklist covering approved tools, data rules, human review, disclosure, accuracy, and accountability. The outline below gives you a working starting point you can adopt in an afternoon. Heavy policies go unread, and an ignored rule protects no one, so the aim is the lightest version that covers your real risks, written plainly enough that people can recall it in the moment they need it. Governance should match your size and risk rather than mimic a large enterprise: a two-person shop and a regulated clinic need very different depth, but both benefit from the same core of clear data rules, a human-review step, and someone accountable. If you only enforce two rules, make them the data rule and the human-review rule, since they prevent the leaks and public errors that do the most damage. This guide gives you the full checklist, shows how to pair each rule with an owner, and explains how to connect it to daily habits so it actually gets followed.

Why lightweight governance works

Heavy policies go unread. A short, clear checklist gets followed, which is what actually reduces risk. The Stanford HAI AI Index tracks responsible-AI issues that scale down to practical rules for any business.

The governance checklist

1. Approved tools: list what is allowed; others need sign-off.
2. Data rules: what must never be pasted into public tools.
3. Human review: which outputs require sign-off before use.
4. Disclosure: when to tell customers AI was involved.
5. Accuracy: the requirement to fact-check claims and numbers.
6. Accountability: who owns AI-assisted work and the policy itself.
7. Review cadence: when you revisit the rules.

Pair each rule with an owner

A rule with no owner is a suggestion. Name who maintains the tool list, who handles disclosure questions, and who reviews high-stakes output. Our companion governance checklist shows how the pieces connect.

Keep data and review front and center

If you only enforce two rules, make them the data rule and the human-review rule. They prevent the leaks and the public errors that do the most damage. The Pew Research work on AI underscores why both matter for customer trust.

Roll it out simply

1. 1

   Adopt the outline

   Fill each item with your specifics in plain language..

2. 2

   Assign owners

   Name who is responsible for each rule..

3. 3

   Share and acknowledge

   Send it and ask people to confirm they read it..

4. 4

   Review quarterly

   Update as tools and rules change..

Right-size the governance to your business

Governance should match your size and risk, not mimic a large enterprise. A two-person shop and a regulated clinic need very different depth, but both benefit from the same core: clear data rules, a human-review step, and someone accountable. Start with the lightest version that covers your real risks, and add detail only where a genuine concern justifies it. The aim is a document people actually follow, because over-engineered governance gets ignored and ignored rules protect no one.

If you handle sensitive or regulated data, weight the data and disclosure sections more heavily and consider a short review by someone who knows your field's rules. For most small businesses, though, a plain checklist with named owners is enough to prevent the common problems. Broad research such as the Stanford HAI AI Index tracks responsible-AI issues that scale down cleanly to these practical rules.

Connect the checklist to daily habits

A checklist only works if it shows up in the workflow. Tie the data rule to onboarding and the prompt library, attach the review step to the tasks that need it, and make the disclosure rule part of how customer-facing work ships. When governance lives inside the daily process rather than in a forgotten document, it protects you without anyone having to remember a policy. For broader economic context on why responsible adoption matters, see the IMF analysis on AI.