Free AI Policy Template

An AI policy is a written rule covering how staff may use artificial intelligence tools for work. It names which tools are allowed, what information may go into them, and what has to happen before AI output reaches a customer.

The document exists because these tools sit outside your normal controls. An employee pasting a client list into a chatbot has moved that data somewhere you did not choose and cannot audit.

Coverage should be broad. Writing assistants, code generators, image tools, meeting transcribers, and features quietly built into software your team already pays for all belong inside scope.

Treat it as a working document rather than a statement of principles. Staff need to know what they may open on Monday, not what your business believes about technology in general.

Note what this document does not attempt. It governs your own staff rather than the tool vendors, so read their terms separately.

Size is not the deciding factor either. A five-person business handling client information faces the same leak risk as a large one, just with fewer people to notice it happening.

Adoption arrived faster than governance did, and most teams started using these tools before anyone approved them.

Three risks drive the urgency. Confidential information leaks into systems that may retain it. Output that reads confidently turns out to be wrong. Ownership of generated material gets murky when nobody tracked how it was made.

None of those risks are theoretical. A convincing but invented statistic in a client proposal costs credibility immediately, while leaked customer data can cost considerably more.

Client and customer expectations add pressure too. Contracts increasingly ask suppliers what internal controls they have, and pointing at a written document answers that question quickly.

Silence is itself a decision. Without written guidance, every employee sets a personal standard, and those standards will differ wildly across your business.

The upside matters as well, though. Staff who know exactly what is permitted use these tools more confidently, so an AI policy tends to increase sensible adoption rather than suppress it.

Concrete guidance beats broad principles here, because staff need to know what they may actually do on Monday morning.

Approved Tools

List them by name. Also explain how someone requests approval for a tool that is not yet on your list.

Data That Must Never Be Entered

Customer records, employee details, financial data, unreleased plans, credentials, and anything covered by a confidentiality agreement.

Human Review Requirements

Say which uses need checking before anything leaves the business. Draft emails may need a glance, while published claims need verification.

Disclosure

When AI involvement gets mentioned to clients, colleagues, or candidates. Recruitment and customer support deserve particular attention, since people reasonably want to know whether a person or a system assessed them.

Ownership and Third-Party Material

Who owns the output, and how staff avoid publishing material that closely reproduces someone else’s work.

Prohibited Uses

Decisions about hiring, discipline, pay, or credit are common exclusions, since automated judgments about people carry heightened risk.

Training and Questions

Who staff ask when something falls outside the rules, and how new starters learn the expectations during onboarding.

Most weak documents fail the same handful of ways.

Banning everything outright rarely works. Staff continue anyway on personal accounts, and now the activity is invisible to you.

Ignoring embedded features is another frequent miss. Your existing software may have added AI functionality without anybody reviewing it.

Vague verification language causes the rest. Telling people to check output for accuracy means nothing until you say who checks, against what, and at which point.

Free personal accounts deserve a mention as well. Consumer versions of the same tool often carry different data terms from the business version you approved, and staff rarely notice the difference.

Finally, watch for silent scope creep. A writing assistant approved for internal notes gradually ends up drafting client deliverables unless somebody states where the boundary sits.

This is the one workplace document that ages in months rather than years.

Set a short review cycle. Quarterly suits most businesses, since tools, features, and vendor terms all shift quickly.

Name an owner. Somebody has to watch for new tools appearing inside existing software, and that responsibility disappears unless it belongs to a named person.

Revisit the approved list at each review. Tools get acquired, change their terms, or add features that shift the risk picture entirely.

Watch the legal picture as well. Rules covering artificial intelligence, automated decisions, and data handling are actively developing across different states and sectors, so check your state’s official website and take advice before relying on your own reading.

Tell people when the AI policy changes. A quiet update nobody announced has roughly the same effect as no document at all.

Nothing on this page states any state’s law on artificial intelligence, automated decisions, data protection, or intellectual property.

Document Genius walks you through each section with simple questions, so a first draft takes an afternoon.

1. Survey which tools your team already uses.
2. Decide your approved list, plus the route for requesting additions.
3. Write the do-not-enter data rules in plain, specific language.
4. Set human review requirements for each type of output.
5. State your disclosure expectations and prohibited uses.
6. Assign an owner and a review date, then circulate it widely.

Build your AI policy now and give your team something clear to work from.