AI Governance Policy: Template, Components & Examples
An AI governance policy is the foundational document that sets out your organization's principles, roles, and rules for AI use. This guide covers every section you need and how to align it to current AI regulations.
What Is an AI Governance Policy?
An AI governance policy is a board-approved document that sets out an organization's principles for AI use, the governance structures responsible for AI oversight, the standards AI systems must meet before deployment, and the processes for managing AI-related risks and incidents.
It is typically the top-level document in an AI governance program — a policy rather than a procedure — that delegates implementation details to subordinate standards, guidelines, and playbooks.
Key Sections of an AI Governance Policy
A complete AI governance policy should include the following sections:
- Purpose and Scope — what the policy covers, which AI systems and organizational units are in scope, and what is explicitly excluded.
- Principles — the organization's core AI principles (fairness, transparency, accountability, safety, privacy) that all AI development and deployment must uphold.
- Governance Structure — the roles and bodies responsible for AI governance: board committee, Chief AI Officer, AI governance committee, business unit AI leads.
- AI System Lifecycle Requirements — standards for AI system discovery, risk assessment, approval, deployment, monitoring, and decommissioning.
- Prohibited Uses — categories of AI use that are prohibited, regardless of technical capability (e.g., social scoring, biometric surveillance without consent).
- Incident Reporting — how AI-related incidents must be reported internally and, where required, to regulators.
- Third-Party AI Management — requirements for AI vendor due diligence, contract terms, and ongoing compliance monitoring.
- Training and Awareness — AI governance training requirements by role.
- Compliance and Enforcement — how compliance with the policy is monitored and what happens when violations occur.
- Review Cycle — how often the policy is reviewed and who approves revisions.
Regulatory Requirements for AI Governance Policies
Several AI regulations either explicitly require an AI governance policy or implicitly require one by mandating a 'governance program' or 'risk management system' without which the specific obligations cannot be fulfilled.
- TRAIGA (Texas) — does not mandate a governance program for private deployers, but a documented governance policy is core evidence of substantial compliance with the NIST AI RMF, the § 552.105(e) safe harbor against Attorney General enforcement.
- ISO/IEC 42001 — Clause 5.2 explicitly requires top management to establish an AI policy.
- NIST AI RMF — the Govern function establishes AI risk governance, which NIST says should include documented policies.
Frequently asked questions
Does an AI governance policy need board approval?
Best practice — and an increasing regulatory expectation — is that the AI governance policy is approved by the board or a board committee. This signals organizational commitment and creates clear accountability at the highest level.
How long should an AI governance policy be?
A top-level AI governance policy is typically 5–15 pages. It sets principles, roles, and requirements at a high level and references subordinate standards and procedures for implementation details. Avoid embedding too much operational detail in the policy itself — that creates maintenance overhead as procedures evolve.
What is the difference between an AI governance policy and an AI use policy?
An AI use policy governs how employees may use AI tools in their work (e.g., approved LLM tools, data handling rules). An AI governance policy governs how the organization manages AI systems it develops or deploys. Both are needed; they address different audiences and risk surfaces.
Can TRAIGA generate an AI governance policy?
TRAIGA includes a policy generator that creates a customized AI governance policy based on your organization's size, industry, AI system inventory, and applicable regulations. The generated policy is aligned to TRAIGA (Texas), NIST AI RMF, and ISO 42001.
Related resources
Checklist
AI Governance Checklist
Step-by-step checklist including policy adoption (step 3).
Guide
What Is AI Governance?
Foundational guide to AI governance concepts and best practices.
Guide
AI Governance Framework
How to select and implement an AI governance framework.
Article
Blog: AI Governance Policies Explained
Deep-dive article on writing AI governance policies.
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