Many employees are already using AI tools at work, whether or not the company has approved any. That is the real reason to write an AI policy. It gives people clear rules before something goes wrong, and it does not require a legal team or a 30-page document.
This guide covers what a short, practical policy should include, with a simple starting point you can adapt. It is general business guidance and not legal advice, so have counsel review anything that touches regulated data.
Why a short policy beats no policy
Without rules, each person decides for themselves what is safe to paste into an AI tool. Some will be careful and some will not, and you will not know which is which. A one-page policy replaces guesswork with a shared standard, and it is short enough that people will read it.
What to include
- Approved tools. List the tools staff may use for work, and how to request a new one. Review each tool for security, data handling, and support before you approve it.
- Data rules. Say what must never be entered into an AI tool unless it is specifically approved: customer personal information, passwords and credentials, financial records, contracts, and anything covered by a confidentiality agreement.
- Human review. AI output can be confident and wrong. Require a person to check anything that goes to a client, a regulator, or the public.
- Disclosure. Decide when clients or partners should be told that AI helped produce work, and follow any rules in your contracts.
- An accountable owner. Name one person who answers questions, approves tools, and updates the policy.
- Reporting. Tell staff what to do if they paste something they should not have. A fast report is better than a hidden mistake.
A simple do and do not list
- Do use approved tools for drafting, summarizing, and brainstorming.
- Do check facts, numbers, and names before you rely on AI output.
- Do ask before using a new AI tool with company information.
- Do not enter customer data, credentials, or confidential documents into unapproved tools.
- Do not send AI-generated work to a client without reading it first.
Roll it out so it sticks
A policy only helps if people know it exists. Walk your team through it in a short session, use real examples from your own workflows, and repeat the main points when new tools arrive. Leadership should follow the same rules, because teams copy what their leaders do. Review the policy every few months, since the tools change quickly.
Questions to ask before approving a tool
- Where is our data stored, and who at the vendor can see it?
- Is what we enter used to train the vendor’s models, and can we turn that off?
- Does the tool have admin controls, user permissions, and activity logs?
- Can we export or delete our data if we stop using it?
- Does it meet any compliance rules that apply to our industry or our clients?
Write the answers down. Then when someone asks whether a tool is approved, you can point to a record and not a memory.
Start with what people already use
Before you publish rules, find out which tools your team already uses. A short, friendly survey works well, and you should make clear that the goal is to build a safe list, not to discipline anyone. Many of the tools people mention will be worth approving, and the rest give you a chance to explain the risks.
Common mistakes to avoid
- Banning everything. A blanket ban pushes AI use out of sight, where you cannot guide it.
- Writing a long document. A policy nobody reads protects nobody. One or two pages is plenty to start.
- Skipping the owner. Without one accountable person, questions go unanswered and the policy goes stale.
- Setting it and forgetting it. New tools and features arrive constantly, so review the policy every few months.
Need help putting AI guardrails in place?We help businesses review tools, write practical policies, and train their teams. Start with a free technology assessment.
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