How to Write an AI Usage Policy for Your Company

An AI usage policy is a short internal document that sets out which AI tools employees can use, for what work, with what data and under what checks. A good policy brings clarity more than prohibitions: it states plainly which tools are approved, which kinds of data must never be shared, when human review is required and who is responsible for what. A policy of one or two pages, backed by examples, is far more effective than a long document nobody reads.

Without a policy, employees either don't use AI at all and miss the opportunity, or they use it on personal accounts with no rules. The second case creates an invisible risk for data security and for compliance with privacy laws such as KVKK (Turkey's data protection law). A policy is the cheapest way to remove that uncertainty.

Why do you need an AI usage policy?

A policy has three core goals:

• Managing risk: Preventing personal data, trade secrets and customer information from flowing uncontrolled into third-party tools.
• Protecting quality: Keeping AI-generated content from going out the door without being checked.
• Encouraging use: Spreading safe usage by answering employees' "am I allowed to use this?" question.

The third goal is often forgotten. If the policy is nothing but prohibitions, employees see it as an obstacle. Writing down which kinds of work are encouraged makes the policy much easier to adopt.

The core sections of the policy

1. Scope and definitions

State who the policy covers (employees, interns, outside consultants) and which tools (chat assistants, image generators, AI features built into other apps). Clarify what you mean by "AI tool" with a short definition.

2. Approved tools list

List the tools, and their versions, that can be used with company data. Explain what review a tool goes through before it's added (data processing terms, security, cost) and who to send new tool suggestions to. Keeping the list on a separate page and updating it regularly is more practical than changing the policy itself all the time.

3. Data classes

This is the most critical section. For most companies, three simple categories are enough:

Class	Examples	Use in AI tools
Public	Published content, general information	Allowed in all approved tools
Internal	Internal correspondence, draft documents, reports without personal data	Only in tools with an approved enterprise version
Confidential	Personal data, customer information, financial data, contracts, source code, trade secrets	Prohibited unless specifically approved; anonymized if needed

Giving concrete examples for each class helps employees make the right call in gray areas.

4. Human review and accountability

State clearly that the employee who uses AI-generated content is responsible for it. Specify that anything going to customers, the public or management must be read before it's sent, and that specific claims must be verified. Add that in decisions with consequences for people (hiring, performance, credit, pricing), AI may only be used as an aid.

5. Transparency

Define when AI use must be disclosed. For example, a chatbot that talks directly with customers should say it's a bot, and realistic images should be labeled as AI-generated where necessary.

6. Intellectual property

Set rules that AI-generated content must respect third-party copyrights, must not imitate other brands' or artists' work, and that the company's confidential source code or designs must not be entered into external tools.

7. Violations and incident reporting

Explain what an employee should do, and whom to tell, if confidential data is shared by mistake. Emphasizing that reporting won't be punished, and that quick reporting is actually encouraged, keeps incidents from being hidden.

8. Training and updates

Specify how the policy will be announced, how it will be explained to new hires and how often it will be reviewed. Since AI tools change quickly, at least one review a year, ideally two, is reasonable.

A short policy template you can adapt

The template below is a starting point for small and mid-sized teams. It isn't a legal document; adapt it to your company and have your legal advisor review it if needed.

[COMPANY NAME] AI USAGE GUIDELINES

1. Purpose: To use AI tools safely and responsibly to make our
   work easier.
2. Approved tools: Only the tools listed at [list link] may be used
   with company data. Personal accounts are not used with work data.
3. Data that must never be entered: Personal data of customers and
   employees, ID and contact details, health information, financial
   account details, contracts, source code, passwords.
   If needed, replace names and numbers with placeholders such as
   [CUSTOMER] or [AMOUNT].
4. Review: Whoever uses AI output is responsible for the content.
   Numbers, dates, names and sources in outgoing text are verified.
5. Decisions: In significant decisions about hiring, performance and
   customers, AI only makes suggestions; a human makes the decision.
6. Transparency: Automated systems that talk to customers disclose
   that they are bots.
7. Reporting: If you share confidential data by mistake, report it
   to [person/email] the same day.
8. Suggestions: Send ideas for new tools or uses via [channel].
Last updated: [date] – Owner: [name/role]

Putting the policy into practice

A written policy is useless if no one follows it. To get it adopted:

• Hold a short kickoff session: Walk through the policy with concrete examples in a 30-minute meeting.
• Build an examples library: Create a page of "this is acceptable / this isn't" examples.
• Make it easy to find: Keep the policy in your internal wiki or a shared folder where everyone can find it.
• Open a questions channel: Name a person or channel where employees can quickly ask about gray areas.
• Collect feedback: Find out where the policy makes work unnecessarily hard, and update it.

Common mistakes

• A total ban: It leads employees to keep using AI on personal tools, out of sight.
• Too much text: Nobody reads a ten-page policy, and the critical rules get lost.
• Rules without examples: "Don't share sensitive data" gets interpreted differently by everyone unless you explain what counts as sensitive.
• An outdated list: Once the approved tools list goes stale, employees start ignoring it.
• No clear owner: If nobody owns the policy, questions go unanswered and updates never happen. A specific person or role should be explicitly responsible for keeping it current.
• Managers not leading by example: When managers don't follow the rules, employees don't take the policy seriously either. Having the leadership team adopt it first speeds up its spread.

If you want your team to use AI through internal systems built on infrastructure that enforces your policy rules technically (for example, an internal assistant that automatically masks personal data), we build that kind of solution as part of our custom software services.

Conclusion

An AI usage policy is a prerequisite for your team to use these tools safely and productively. Gather your approved tools, data classes, human review requirements and reporting process into a short document with examples. Don't write it once and forget it; update it as tools and needs change, and take your employees' feedback into account.