AI Governance Policy Template
A practical starting structure for defining acceptable AI use, data boundaries, and approval authority — built to be adapted, not adopted word for word.
This template is not a finished policy. It's a structure that saves you from starting on a blank page, organized around the questions a use policy actually needs to answer before it can be applied to a real tool.
How to Use This Template
Work through each section in order. Where a section asks you to classify data or set an authority threshold, use your organization's actual categories rather than generic examples — the template only becomes useful once it reflects your real data classification and reporting lines.
Before you start
This template assumes some AI use is already happening informally. If you haven't yet taken an inventory of what's in use today, that's worth doing first — a policy built without knowing what it needs to cover will miss the tools already creating exposure.
Section 1: Purpose and Scope
Purpose Statement
Draft here: Why this policy exists — typically framed around enabling productive AI use while protecting privileged, confidential, and sensitive information.
Scope
Draft here: Which teams, tools, and use cases this policy governs — including whether it covers embedded vendor AI features, not just standalone AI products.
Section 2: Data Classification and Boundaries
| Data Category | AI Use Permitted? | Conditions |
|---|---|---|
| Privileged material | Define your rule here | Define your conditions here |
| Personally identifiable information | Define your rule here | Define your conditions here |
| Unreleased corporate information | Define your rule here | Define your conditions here |
| General business correspondence | Define your rule here | Define your conditions here |
Replace each row's placeholder with your organization's actual data classification tiers, and be explicit about what "permitted" means — fully permitted, permitted with human review, or not permitted at all.
Section 3: Approval Authority
Low-Risk Use
Draft here: Who can approve internal, low-sensitivity AI use without escalation.
Moderate-Risk Use
Draft here: Who reviews use cases involving sensitive data or client-facing output.
High-Risk Use
Draft here: What triggers escalation to General Counsel or a governance committee.
Section 4: Human Verification Requirements
Draft here
Specify which categories of AI-assisted output require human review and sign-off before use — for example, any output relied upon in a client deliverable, filing, or external communication.
Section 5: Review and Update Cycle
Policy Review Frequency
Draft here: How often the policy itself is reassessed — commonly annually, or triggered by a material change in AI capability.
Use Case Reassessment
Draft here: How often approved tools are revisited, and what triggers an earlier reassessment — such as a vendor feature change.
Next Step
Once this structure is filled in, the policy becomes the standard every new tool gets measured against inside the governance workflow. Pair it with the AI Risk Assessment Checklist to apply it consistently to specific tools as they come up for review.
A template only becomes a policy once it reflects decisions your organization has actually made. Treat the blanks as the real work.