How Do I Create an AI Acceptable Use Policy?

Quick answer: An AI acceptable use policy defines which AI tools employees can use, what data can go into them, and how to use AI responsibly. Without one, you have no governance—just hope. Here's how to build one that works.

Why You Need This Now

Every day without a policy:

• Employees use AI tools you haven't vetted
• Sensitive data flows to unknown destinations
• You can't enforce rules you haven't set
• "I didn't know" becomes the defence

An AI policy isn't bureaucracy. It's the foundation of AI governance.

What to Include

1. Approved AI tools

Be specific:

• Approved for general use: [List tools, e.g., Microsoft Copilot, approved ChatGPT Enterprise]
• Approved for specific purposes: [e.g., GitHub Copilot for developers only]
• Prohibited: [Public ChatGPT, Claude consumer, unapproved tools]
• Approval process: How to request new tools

Don't say "use appropriate tools." Define which tools are appropriate.

2. Data classification for AI

What can and cannot go into AI tools:

Never input into any AI:

• Customer personal data
• Financial records
• Health information
• Credentials or access tokens
• Classified or restricted information
• Source code (unless approved developer tools)

Allowed with approved enterprise tools:

• General business writing
• Public information
• Anonymised/synthetic data
• Content you'd share externally anyway

Grey areas (require judgment):

• Internal strategies (consider competitive risk)
• Contract drafts (after removing sensitive details)
• HR matters (heavily anonymised only)

3. Verification and accuracy

AI makes things up. Require:

• Human review of all AI outputs
• Fact-checking before external use
• Citation verification
• No direct publication without review

State who's responsible when AI outputs are wrong. (Hint: it's the human who used them.)

4. Intellectual property

Address:

• Who owns AI-generated content
• Copyright implications
• Confidentiality of inputs
• Training data concerns

5. Transparency

When to disclose AI use:

• Customer-facing content
• Legal documents
• Regulatory submissions
• Academic or professional work

Some contexts require disclosure. Define which.

6. Roles and responsibilities

Who does what:

• IT/Security: Approve tools, implement controls, monitor
• Legal: Review contracts, IP implications
• Managers: Ensure team compliance
• Users: Follow policy, report concerns

Common Mistakes

Too vague: "Use AI responsibly" means nothing. Be specific.

Too restrictive: Total prohibition drives shadow AI underground. Provide alternatives.

No enforcement: Policy without monitoring is wishful thinking.

Static document: AI evolves fast. Review quarterly minimum.

No training: People need to understand why, not just what.

Making It Work

Communicate clearly

• All-hands announcement
• Manager briefings
• Easy-to-find documentation
• Regular reminders

Provide alternatives

If you prohibit public ChatGPT, provide Copilot. People need to do their jobs.

Implement technical controls

Policy without enforcement is suggestion. DLP, web filtering, monitoring.

Monitor and adapt

Track AI tool usage. Update policy as landscape changes. New tools appear constantly.

Enforce consistently

Inconsistent enforcement undermines policy. Define consequences, apply them.

Sample Policy Structure

1. Purpose and scope
2. Definitions (what we mean by "AI tools")
3. Approved tools list
4. Prohibited uses
5. Data handling requirements
6. Accuracy and review requirements
7. Intellectual property
8. Transparency and disclosure
9. Roles and responsibilities
10. Reporting concerns
11. Consequences of violation
12. Review and update schedule

What We Help With

• Policy development tailored to your organisation
• Technical implementation of controls
• Training for staff
• Monitoring and reporting
• Ongoing governance support

A good AI policy balances protection with productivity. We help you find that balance.

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about policy and implementation.

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