What Is an AI Acceptable Use Policy?
An AI Acceptable Use Policy (AUP) is a document that defines how employees and contractors may use AI tools within your organization. It establishes boundaries, expectations, and requirements for responsible AI use.
A well-crafted AUP protects your organization from misuse while enabling productive AI adoption. It's the foundation of AI governance documentation.
Why You Need an AI Acceptable Use Policy
Risk Mitigation
Without clear guidelines, employees may inadvertently expose sensitive data, create legal liability, or damage customer relationships through inappropriate AI use.
Regulatory Readiness
Regulations like the EU AI Act require documented policies. Having an AUP demonstrates governance maturity.
Consistent Practices
A policy ensures everyone follows the same rules, reducing variation and improving accountability.
Key Sections to Include
1. Purpose and Scope
Define what the policy covers and who it applies to. Be specific about:
- Which AI tools are covered
- Who must follow the policy
- When it applies (work hours, personal devices, etc.)
2. Approved Tools and Use Cases
List explicitly approved AI tools and their permitted uses:
- Approved tools (e.g., "ChatGPT for internal research only")
- Approved use cases (e.g., "Draft generation, not final client deliverables")
- Approval process for new tools
3. Prohibited Uses
Clearly state what is NOT allowed:
- Processing client confidential data
- Generating legal or medical advice
- Creating content without human review
- Bypassing security controls
4. Data Handling Requirements
Specify rules for data used with AI tools:
- What data can be input to AI systems
- Classification requirements
- Privacy and consent requirements
5. Human Oversight Requirements
Define when human review is required:
- All client-facing outputs
- Decisions affecting individuals
- Content that will be published
6. Incident Reporting
Explain what to do when things go wrong:
- What constitutes an incident
- Who to report to
- Timeline for reporting
7. Consequences
State the consequences of policy violations:
- Warning and retraining
- Access revocation
- Disciplinary action
Common Policy Mistakes
Mistake 1: Being Too Vague
Policies that say "use AI responsibly" without specifics don't help anyone. Be concrete.
Mistake 2: Being Too Restrictive
Overly strict policies drive shadow AI use. Balance protection with enablement.
Mistake 3: Not Training on the Policy
A policy no one knows about is worthless. Invest in awareness and training.
Next Steps
Generate your customized AI Acceptable Use Policy using our free Policy Generator tool. Then consider the full Documentation System for comprehensive governance documentation.