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AI use policy in the company: what it should include
An AI use policy is the document that tells staff which artificial intelligence tools they may use, what information they must not share with them, which uses need prior approval, and what to do if something goes wrong. It is the fastest way to move from spontaneous AI use to use with common rules—without banning it.
Why it is needed
In most organizations, teams already use generative AI assistants to draft, summarize, or analyze—often with personal accounts. None of that is negative in itself. The problem appears when no one knows what information is leaving the organization or who reviews what the AI produces.
Banning AI does not work either: teams keep using it, now without visibility, and the organization gives up productivity gains. A clear policy addresses both.
AI policy and responsible-use policy: not the same thing
In a management system based on ISO/IEC 42001, it helps to distinguish two documents:
| AI policy | Responsible-use policy | |
|---|---|---|
| For whom | Leadership and system owners. | All staff. |
| What it defines | What the organization uses AI for, with which principles, what commitments it makes, and who is accountable. | What each person may and may not do when using AI tools at work. |
| Who approves it | Leadership. | Leadership or the AI management system owner. |
| Tone | Strategic. | Practical and concrete, with examples. |
This article focuses on the second: the one teams read and apply every day.
Ten points it should cover
1. Purpose and scope
Why the policy exists and who it applies to: employees, contractors, and anyone using AI tools on behalf of the organization.
2. Authorized tools
A list of approved AI tools, with the version or account type allowed (for example, the corporate account—not a personal one). Also the path to request a new tool.
3. Information not to share
The most important point. It must state clearly what information must not be entered into external AI tools, for example:
- Personal data of clients or staff, protected by applicable data-protection rules.
- Non-public financial, strategic, or contractual information.
- Source code, credentials, and passwords.
- Information received from third parties under confidentiality.
It works best if it aligns with information classification the organization already uses.
4. Uses that require prior approval
Not all uses carry the same risk. Those that intervene in decisions about people (hiring, credit, claims handling), those communicated directly to clients, or those that automate critical processes should go through assessment before use.
5. Human oversight and validation of results
AI supports decisions; it does not replace them. The policy should make clear that whoever uses an AI tool is responsible for the result and must verify accuracy before using it in a report, client response, or decision.
6. Transparency
When to disclose that content or a response was generated with AI support, especially toward clients.
7. Intellectual property and confidentiality
What happens to output produced with AI, how third-party rights are respected, and which vendor terms matter.
8. Incident and concern reporting
A clear channel to report errors, information leaks, or misuse, and to ask questions. Without blame: the goal is to learn in time.
9. Training
What training each profile receives. Leadership, business users, and technical teams need different knowledge.
10. Owners and review
Who owns the policy, how often it is reviewed, and how changes are communicated. AI tools change quickly; the policy should too.
Common mistakes
- Copying a generic template without adapting it to the organization’s real tools and data.
- Writing it only in legal tone. If teams do not understand it, they do not apply it. Concrete examples help more than clauses.
- Publishing it and forgetting it. Without communication and training, the policy sits in a file no one opens.
- Writing it without knowing which AI is in use. Before writing rules, inventory the AI tools and features present in the organization.
How it fits in an AI management system
The responsible-use policy is one of the first pieces of a management system based on ISO/IEC 42001. In the AI with Judgment methodology it is worked in the leadership and policy phase, together with the AI policy and assignment of owners, supported by a responsible-use workshop for teams.
It is also one of the most direct answers to the five questions every leadership team should be able to answer about AI use.
This article is for information only and does not replace legal advice.