AI Governance Policy Template: A Practical Starting Point
A usable AI governance policy template covering approved tools, data handling rules, and review responsibilities - free to copy and adapt, no signup required.
Most AI governance policies fail for the same reason: they're written as a memo nobody reads instead of a set of rules that actually match how people already work. This is a starting template, not a finished legal document - adapt it with your own legal and compliance review before adopting it.
Quick Answer
A practical AI governance policy covers five things: which AI tools are approved for use, what categories of data can and can't be shared with them, who reviews AI-generated outputs before they're used externally, how usage is logged for audit purposes, and what happens when someone needs a tool that isn't yet approved. Skipping the last one is the most common reason policies fail - without a fast path to approve new tools, people route around the policy instead of following it.
The template
1. Approved tools
List the AI tools your organization has reviewed and approved, by name. Anything not on this list is not approved for work data, full stop - ambiguity here is where shadow AI starts.
2. Data classification rules
Define, explicitly, what can and cannot be shared with an approved AI tool:
- Never share: PII, PCI/payment data, credentials, material nonpublic information, anything covered by a signed NDA with a third party.
- Share with caution, masked where possible: internal financial figures, unreleased product details, aggregate customer data.
- Generally fine to share: publicly available information, drafts of already-public content, general research questions.
3. Review responsibility
State who reviews AI-generated content before it's used in a client-facing, regulatory, or public context - and what that review actually checks for (factual accuracy, data handling compliance, tone).
4. Logging and audit trail
Specify what gets logged: which tool was used, roughly what kind of task, and whether any regulated data categories were involved. This doesn't need to be invasive - it needs to exist.
5. Fast path for new tool requests
Give employees a real, quick way to request approval for a new tool, with a stated response time. Without this, the policy becomes something people work around instead of something they follow.
Why the "fast path" section matters most
A governance policy with four strong sections and no fast-approval path will still get bypassed the first time someone needs a tool that isn't on the list yet and can't wait two weeks for a committee review. The tools change faster than most governance processes can keep up with - build the exception process in from the start.
FAQ
How often should this policy be updated?
Review the approved tools list at least quarterly - the AI tool landscape changes fast enough that a yearly review will leave real gaps.
Does this apply to AI features built into other software, not just standalone AI tools?
Yes - AI features inside a CRM, an email client, or a productivity suite should go through the same approval and data-classification review as a standalone AI tool.
Read next
What is AI agent governance? and what is shadow AI? cover the concepts behind this template in more depth.
See how this applies in practice with Dapto Workbench - an AI work platform for reports, documents, data checks, and other repeatable business work.
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