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What Should an AI Policy Include? Essential Components Explained

October 11, 20259 min readMichael Lansdowne Hauge
For:HR LeadersCompliance OfficersIT ManagersBusiness Owners

Complete guide to AI policy components: purpose, scope, principles, acceptable use, data handling, risk management, and more. Includes policy checklist.

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Key Takeaways

  • 1.Every AI policy needs clear scope defining which tools and use cases it covers
  • 2.Include data handling rules specifying what information employees can share with AI
  • 3.Define approval workflows for new AI tool adoption and high-risk applications
  • 4.Establish accountability by assigning policy ownership and violation procedures
  • 5.Build in regular review cycles to keep pace with rapidly evolving AI capabilities

What Should an AI Policy Include? Essential Components Explained

Executive Summary

  • An AI policy establishes rules and guidance for AI use across your organization
  • Essential components include: purpose, scope, principles, acceptable use, data handling, and accountability
  • Policy complexity should match organizational needs—don't overcomplicate for small-scale AI use
  • A good policy balances enablement with risk management—not just restrictions
  • Policies should be living documents, reviewed and updated regularly
  • This guide covers what to include, why it matters, and how to structure your policy

The 11 Essential Policy Components

1. Purpose and Objectives

Why the policy exists and what it aims to achieve.

2. Scope

Who and what the policy covers, including definitions.

3. Principles

The values guiding AI use (human-centered, transparent, fair, secure, accountable).

4. Acceptable Use

What AI use is permitted and prohibited.

5. Data Handling

How data is used with AI systems.

6. Risk Management

How AI risks are identified and managed.

7. Approval Processes

How new AI use is authorized.

8. Roles and Responsibilities

Who is accountable for what.

9. Training Requirements

What training is required for AI users.

10. Compliance and Enforcement

Consequences and compliance monitoring.

11. Incident Reporting

Response when things go wrong.


AI Policy Components Checklist

Foundation

  • Purpose statement
  • Clear scope (who, what)
  • Key definitions
  • Governing principles

Rules and Guidance

  • Acceptable use guidelines
  • Prohibited activities
  • Data handling requirements
  • Generative AI specific guidance

Governance

  • Risk management approach
  • Approval processes
  • Roles and responsibilities
  • Training requirements

Operations

  • Compliance monitoring
  • Enforcement approach
  • Incident reporting
  • Exception process

Administration

  • Policy owner
  • Review cycle
  • Version control

Scaling Policy Complexity

Organization TypeApproach
Small business (<50)1-2 page essential policy
Mid-size business3-5 page comprehensive policy
EnterpriseFull policy suite
Regulated industryDetailed regulatory policies

Frequently Asked Questions


Disclaimer

This article provides general guidance on AI policy development. Organizations should consult legal and compliance professionals for specific requirements in their jurisdictions.


Next Steps

Book an AI Readiness Audit with Pertama Partners for help developing or reviewing your AI policy.


Frequently Asked Questions

Long enough to be clear, short enough to be read. For most organizations, 2-5 pages for core policy, with appendices for detail.

Michael Lansdowne Hauge

Founder & Managing Partner

Founder & Managing Partner at Pertama Partners. Founder of Pertama Group.

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