Write an employee AI policy that names approved tools, sets clear data-handling rules, requires human review, and routes sensitive or high-impact uses for approval. Then spell out when to disclose AI assistance, how to report problems, and who maintains the rules. There is no universal template: adapt the policy to your organization’s work, jurisdictions, contracts, and risk tolerance.
Start with the decisions your policy must make
A useful policy answers practical questions employees face before, during, and after using a generative AI tool: May I use this service for work? What information may I enter? Who must check the result? When do I need approval or disclose AI assistance? What should I do if something goes wrong?
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Use those questions to define the policy’s scope and approval routes before drafting detailed rules. The NIST AI Risk Management Framework is voluntary, not an employee-policy template. NIST’s Generative AI Profile, released July 26, 2024, offers risk-management actions organizations can adapt to their goals and resources. NIST also says the broader framework is being revised. NIST AI Risk Management Framework · NIST Generative AI Profile
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Choose how employees can access AI
Your policy can restrict AI use in different ways. These are design choices, not approaches that NIST or another cited source has ranked as universally best.
#1 Best Overall
| Approach | What it allows | Trade-off |
|---|---|---|
| Ban | Prohibits employee use of generative AI for work, or in specified work contexts. | Simple to communicate, but limits experimentation and may be difficult to enforce if staff use tools outside approved channels. |
| Unrestricted use | Allows employees to choose tools and use cases, subject to existing workplace rules. | Offers flexibility but leaves employees to judge tool security, data handling, and appropriate reliance without a dedicated approval framework. |
| Tiered approval | Permits lower-risk uses under baseline rules and requires review or approval for restricted data, consequential decisions, or other designated uses. | Balances flexibility with oversight, but requires the organization to define risk categories and maintain an approval process. |
When choosing, weigh the breadth of permitted uses, sensitivity of data, potential impact on people, review burden, disclosure obligations, and the organization’s jurisdiction and sector.
Write the policy section by section
Purpose, scope, and ownership
State which employees, contractors, business units, tools, and work activities the policy covers. Identify the policy owner, the roles that approve exceptions, and where employees can ask questions. Say whether the policy supplements existing security, privacy, records-retention, intellectual-property, and conduct rules; it should not silently replace them.
Approved tools and accounts
Name the services and account types approved for work, or describe how employees request an evaluation. Tell staff not to assume that a consumer-facing service has been reviewed for company use. Explain what to do if a tool is not listed: for example, pause before using it for work and send a request to the designated owner. A vendor setting or product feature alone does not establish that a particular use or disclosure meets your contracts or legal obligations.
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Define data categories employees can readily recognize and say what is allowed for each. Address company-confidential material, customer and employee information, personal data, regulated information, credentials, and information restricted by contract or law. Specify whether approved tools have different rules from unapproved ones; do not rely on employees to infer that distinction.
Make the rule operational: if employees cannot determine whether information is restricted, they should not enter it until they have checked with the designated privacy, security, or policy contact. Align the wording with existing data-classification, access, retention, and incident-response requirements. Do not promise that a tool’s data-use or retention settings make a disclosure lawful without checking the relevant service terms, contract, and applicable law.
Human review and responsibility
Require a named employee to check generated material before relying on it, sending it outside the organization, publishing it, or using it to make a decision. The reviewer should verify important facts, calculations, citations, and whether the content fits its intended audience and purpose. A generated answer is not verified simply because a tool produced it.
Assign responsibility to the employee or business owner who uses the output; do not leave accountability with the tool or an unnamed team. For higher-risk uses, define the additional reviewer, approval authority, and records to keep before the use begins.
Employment and other decisions affecting people
Set a distinct approval and oversight path before using AI in hiring, evaluation, promotion, discipline, or other consequential decisions. Specify who reviews the proposed use, what human involvement is required, and how the organization will address applicable law and existing decision processes. The EEOC’s background-check guidance is general employment guidance, not AI-specific; it says employment decisions based on background information must comply with federal nondiscrimination law. EEOC: Background Checks—What Employers Need to Know
Disclosure and provenance
Tell employees when they must disclose AI assistance and to whom. Set the trigger based on audience, the nature of the use, contract terms, professional rules, and applicable jurisdiction; a blanket instruction to disclose every use may not fit every context.
For EU-related work, distinguish specific transparency duties from a general company preference. The European Commission’s July 20, 2026 guidance says Article 50 transparency obligations apply from August 2, 2026, to specified AI-system uses. Its companion code describes particular covered content, including certain deepfakes and specified public-interest text without human review or editorial control. These materials do not establish a disclosure requirement for every internal AI-assisted document; check whether the system, role, and content fall within a covered context. European Commission transparency guidance · European Commission Code of Practice on Transparency of AI-generated Content
Copyright and third-party material
Direct employees to follow existing intellectual-property rules and seek review when rights are unclear. Avoid promising that a prompt makes an output copyrightable or that generated material is automatically free of third-party rights. The U.S. Copyright Office’s 2025 report says an AI output may be protected when a human author determines sufficient expressive elements, while prompts alone are not enough by themselves. That U.S. report does not settle the law in other jurisdictions or every infringement question. U.S. Copyright Office report release
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Tell staff how to learn the rules and where to report accidental disclosure, harmful or discriminatory output, a suspected security issue, or another policy breach. Give employees a clear contact or reporting channel and state what to do immediately if restricted information was entered into a tool, following your existing incident-response process.
Name who reviews the policy and how employees will be notified when approved tools, organizational risks, or applicable rules change. The review cadence and update process are organizational choices; NIST’s voluntary framework supports ongoing risk management, not a prescribed schedule. For personal data and UK work, check current law and guidance before stating a definitive compliance position: the ICO says its AI and data protection guidance is under review following the Data (Use and Access) Act, and distinguishes legal interpretation from good-practice recommendations. ICO: About this guidance on AI and data protection
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Turn the draft into rules employees can follow
- Inventory real uses. Ask teams which tools and tasks they already use or want to use, what information is involved, and who may be affected by the result.
- Assign owners. Identify the policy owner and the people authorized to assess tools, review sensitive uses, and handle questions or incidents.
- Set categories and routes. Define approved tools, information categories, routine permitted uses, restricted uses, and the approval path for exceptions or higher-impact work.
- Check existing obligations. Have the appropriate privacy, security, legal, procurement, records, and employment stakeholders check the draft against relevant policies, contracts, sector requirements, and jurisdictions.
- Test it with ordinary scenarios. Ask employees to apply the draft to realistic tasks: summarizing public material, drafting customer communications, processing personal data, and supporting a hiring decision. Revise rules that leave the next step unclear.
- Publish and maintain it. Make the policy easy to find, explain how employees get training and help, and establish who will review it as tools and obligations change.
Check legal claims against the actual use
AI-related obligations depend on jurisdiction, role, system, and use. Avoid converting guidance for a specific context into a universal rule, and do not treat an internal policy as a substitute for checking applicable law. In particular, verify current local requirements before setting rules for personal data, employment decisions, external disclosures, or work governed by customer and professional obligations.
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