AI Use Policy for Employees: what must be included in the document

Where to start

A company's AI policy is not about describing the technology itself, but about who can use the tools, what data must not be entered into them and when a human must check the output. According to AI TrustCERT, such a document organizes AI use across departments and limits divergence between employee practices and organizational requirements.

Minimum that should be in the document

According to Acronis documentation and policy templates published by GC AI and 30Elevate, an effective policy should include several constant elements: scope, approved tools, prohibited data, human oversight, error reporting and enforcement of rules.

• Scope of application - the document must indicate whether it applies only to full-time employees or also to contractors, interns and other persons performing work for the company, as Acronis describes.

• Approved tools and accounts - it is worth specifying particular applications or types of solutions and whether only corporate accounts may be used. IFeelTech emphasizes that the policy can cover both standalone tools and AI features in already used software.

• Prohibited data and sensitive data - the document should clearly state which information must not be pasted into prompts. According to AI TrustCERT and Acronis, this concerns especially confidential or protected information and anything that may reveal trade secrets.

• Human verification - the policy should specify which AI outputs require checking before use, publication or sending to a client. GC AI presents this as a separate block "human review and verification".

How to describe rules without creating an overly long document

Practice described by Promise Legal and Brainstorm Inc. shows that the best policies are short but specific: instead of generalities they indicate classes of data, a list of approved tools, an escalation path and consequences for violations. In Polish conditions it is particularly important to describe who decides when an employee wants to use a new tool or connect it to company data.

It is worth adding three things that distinguish a useful document from a decorative one:

• When a use case must be reported before implementation.
• How to report an error, incident or suspected malfunction.
• When the solution is subject to re-evaluation, for example after a change in data scope or integration with a company system.

What this arrangement delivers in practice

The most useful policy does not try to regulate everything at once. Instead it separates rules for typical tasks, like drafting text sketches or summaries, from risky tasks, such as client communication, sales offers, documents with numbers or integrations with email, drive or CRM, which increase the risk level of data processing.

If the document is to work in business, it should be written so that an employee can answer four questions: is this tool allowed, are these data free to use, does the output require verification, and who to report a concern to. These decisions should be in the policy content, not only general declarations about "responsible AI use".

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