AI policy template: a company AI acceptable use policy you can copy

An AI policy template gives you the rules your staff follow when they use AI tools at work and when your company builds AI into its own products. Below is a complete AI acceptable use policy in twelve sections, from an approved tools list and data rules to human review, customer disclosure, building and buying AI, incidents and training. Fill in every field in [square brackets] and delete what does not apply. After the template, a table maps each section to the NIST AI Risk Management Framework, ISO/IEC 42001 and the EU AI Act, with dates checked on 23 October 2026. It is a starting draft written by engineers, not legal advice: have counsel review it before you adopt it.

Before you fill it in

Three things decide whether people follow it.

1. Make a list of the AI already in use. Ask each team which assistants, copilots, meeting recorders and AI features in existing software they use, and on which accounts. Section 3 is only useful if it starts from what people already do.
2. Name one owner. Pick one person, usually in security, IT, legal or operations, who approves tools, answers questions and runs the review.
3. Write for the person at the keyboard. Most of the value is in sections 3 and 4: which tools, which accounts, which data. If those two sections are clear, most mistakes never happen.

If you only use off-the-shelf tools and keep customer data out of them, you can drop sections 7 and 8 until you build or buy AI for customer-facing work.

The AI acceptable use policy template

Copy from the heading below to the end of section 12.

[Company name] AI acceptable use policy

Version [1.0]. Effective [date]. Policy owner: [name, role]. Approved by [name, role]. Next review: [date, no more than 12 months from the effective date].

1. Purpose and scope

This policy sets out how people at [Company name] may use artificial intelligence tools, and how we build and buy AI systems. Its purpose is to let us use AI productively while protecting our customers, our data, our staff and our reputation.

It applies to all employees, contractors, interns and anyone else working on our behalf ([list any agencies or partners]), on any device, whenever they use an AI tool for [Company name] work or with [Company name] data. It covers AI tools we approve, AI features inside software we already use, and AI systems we build. Where this policy conflicts with a law, regulation or customer contract, the stricter rule applies.

2. Definitions

• AI tool: any software that generates text, images, audio, video or code, or that makes predictions, recommendations or decisions, using a machine-learning model. This includes chat assistants, coding assistants, meeting recorders, AI features in existing software and AI agents.
• AI agent: an AI system that can take actions, such as sending messages, changing records, calling other software or spending money, not only answer questions.
• Approved tool: an AI tool listed in section 3, used through the account type listed there.
• Output: anything an AI tool produces, including actions.
• Customer-facing use: any use where output reaches a customer, prospect, patient, candidate or member of the public without being rewritten by a person.
• Policy owner: the person named at the top of this policy.

3. Approved tools

Only the tools below may be used for [Company name] work. Use them only through the account type listed, signed in with your work identity. Personal accounts and free consumer versions are not approved, even for the same product, unless the table says so.

To request a new tool, send [request form or channel] the tool's name, what you want it for, the data it would touch, and a link to its terms. The policy owner will reply within [10 working days]. Until a tool is approved, do not put any [Company name] data into it.

4. Data rules

Every piece of information belongs to one class. When in doubt, treat it as the higher class.

Never paste, upload or dictate the following into any AI tool unless the policy owner has approved that exact use in writing:

• Passwords, API keys, access tokens, private keys or other credentials.
• Payment card numbers, bank account details or government identifiers such as passport, national insurance or social security numbers.
• Health, medical or biometric information about any person.
• Special category data, such as ethnicity, religion, sexual orientation or criminal records.
• Personal data about customers or staff beyond what the approved task needs.
• Information held under a confidentiality agreement that forbids it.
• Legal advice or material subject to legal privilege.
• Material non-public financial information.
• [Any other category specific to your business or your customers' contracts.]

5. Human review

You are responsible for any output you use, in the same way you are responsible for your own work. Before you rely on an output, check it.

• Facts, figures, quotes and citations: check each against the original source.
• Code: review and test it like a colleague's pull request, including any packages it adds.
• Anything sent outside the company: a person reads it before it is sent, unless the use is listed in section 6 as an approved automated reply.
• Decisions about people: AI output may inform, but a person makes and owns any decision about hiring, performance, pay, credit, pricing for an individual customer, access to services or [other decisions you name]. That person must be able to explain the decision without referring to the AI.
• Actions by AI agents: any agent action that sends money, deletes data, changes a customer record or contacts a customer needs a person's approval first, unless the system owner has documented a lower-risk exception under section 7.

6. Telling customers when they deal with AI

• Any chat, voice or messaging system that talks to customers or the public must tell them they are interacting with an AI system at the start of the conversation, and offer a way to reach a person.
• Images, audio or video generated or altered by AI that show real people, places or events must be labelled as AI-generated.
• Text generated by AI and published to inform the public must be labelled as such unless a person has reviewed and edited it and [Company name] takes editorial responsibility for it.
• Approved automated replies: [list any, with the system that sends them and who reviews a sample, or write None].
• Do not present AI output as a named person's personal work or opinion without that person's agreement.

7. Building AI into our products and processes

This section applies when we build, configure or deploy an AI system, including agents, chatbots, scoring models and AI features in our products.

• Register it. Every AI system has an entry in the AI register kept by [team]: owner, purpose, users, data used, decisions it influences, model, vendor and risk tier.
• Risk review before build. Who could be harmed, what data is used, what the system can do on its own and what happens when it is wrong. Systems rated [high] need approval from [role], and counsel checks whether any law classifies the use as high-risk.
• Evaluations. A written set of test cases with pass thresholds. A release that fails them does not ship. Re-run them after any change to the model, prompt, tools or data.
• Human oversight. Design where a person reviews, approves or can stop the system, with the context and authority to do it.
• Logging. Record inputs, outputs, tool calls and model version for [12 months, or longer if law or contract requires].
• Least privilege. Agents get their own credentials, the minimum access the task needs, an allowlist of actions, and spending and rate limits.
• Security testing. Customer-facing systems and agents with write access are tested for prompt injection and data leakage before launch.
• Change control. Model, prompt and tool changes go through the same review and release process as code.

8. Buying AI tools and AI features

Before we buy or switch on an AI tool or AI feature, [procurement or the policy owner] confirms in writing:

• Whether the vendor uses our inputs or outputs to train its models, and that this is switched off or contractually excluded.
• How long inputs and outputs are kept, where, and how to delete them, and which sub-processors and model providers are involved.
• A data processing agreement is signed where personal data is involved.
• Security evidence, such as a current SOC 2 Type II report or ISO/IEC 27001 certificate, and whether the vendor holds ISO/IEC 42001 certification.
• Admin controls: single sign-on, user management, audit logs and feature restrictions.
• How the vendor announces model changes and incidents, and how we export our data and leave.

9. Reporting AI incidents

Report to [channel, email or form] within [24 hours] if you see or cause any of the following. Report even if you are not sure. Nobody will be penalised for a prompt, honest report.

• Restricted or Confidential data put into a tool that is not approved for it.
• Harmful, false, offensive or biased output that reached a customer or the public.
• An AI agent taking an action it should not have.
• Signs that a tool was manipulated, for example by instructions hidden in a document, email or web page.
• A customer complaint that involves an AI system.

The policy owner sets a severity of [low, medium, high], contains the issue, informs affected people and authorities where required, and records cause and fix in the AI register.

10. Training

Everyone covered completes [Company name]'s AI training before using an approved tool, and a refresher every [12 months]. People who build or run AI systems complete additional training on [evaluations, oversight, security and the rules that apply to their systems]. [Team] keeps a record of who completed which training and when.

11. Ownership, exceptions and review

• The policy owner maintains this policy, the approved tools list and the AI register.
• Exceptions must be requested in writing, approved by [role], time-limited and recorded.
• This policy is reviewed at least every [12 months], and sooner when we adopt a significant new AI system, a law or contract changes what we must do, or an incident shows a gap.
• Breaches of this policy are handled under [disciplinary policy or contractor agreement].
• Questions go to [policy owner's contact].

12. Acknowledgement

I have read the [Company name] AI acceptable use policy, version [1.0], and I agree to follow it. Name: [ ]. Role: [ ]. Date: [ ].

How the template maps to NIST AI RMF, ISO/IEC 42001 and the EU AI Act

Customers and auditors tend to ask about three frameworks. The NIST AI Risk Management Framework (AI RMF 1.0, released 26 January 2023) is voluntary and organises the work into four functions: Govern, Map, Measure and Manage. NIST says it is being revised; its Generative AI Profile (NIST AI 600-1, July 2024) covers generative models. ISO/IEC 42001:2023 specifies requirements for establishing, implementing, maintaining and continually improving an AI management system, and is the standard an accredited body can certify you against. The EU AI Act, Regulation (EU) 2024/1689, is law.

For ISO/IEC 42001, a policy is a starting document, not a management system. Certification needs evidence that controls run, such as risk assessments, records and reviews; the register in section 7 and the incident log in section 9 are where that evidence starts.

What the EU AI Act asks of most companies today

AI literacy (Article 4) has applied since 2 February 2025, according to the Commission's AI Act page, and it covers every provider and deployer, whatever the risk level of the system. The Digital Omnibus on AI, in force since 27 July 2026, rewrote the article. The current text says providers and deployers shall take measures to support the development of AI literacy of their staff and others using AI systems on their behalf, taking into account their knowledge, experience and the context of use, and that this does not require them to guarantee any specific level of literacy for any individual. Section 10 and its training records are how you show those measures.

Transparency (Article 50) rules come into effect in August 2026, according to the Commission. Article 50 requires providers to tell people when they are interacting with an AI system, unless it is obvious, and deployers to disclose deep fakes and AI-generated text published to inform the public, unless a person has reviewed it and someone holds editorial responsibility. Section 6 follows that shape.

High-risk systems, such as AI used in recruitment, credit scoring or access to essential services under Annex III, carry far heavier duties. After the July 2026 amendment those rules apply from 2 December 2027 for Annex III uses and 2 August 2028 for AI in products covered by Annex I (dates checked on 23 October 2026). The Act also reaches companies outside the EU when an AI system's output is used in the EU. Whether a system of yours is in scope, and in which category, is a question for counsel; section 7 makes sure it gets asked before the build.

What this template does not do

It does not tell you which laws apply. Data protection, employment and consumer law and sector rules may add duties or forbid uses this template allows. If you handle patient data, read our guide to HIPAA-compliant AI agents and talk to counsel.

Signing it does not make it true. The tools list needs someone keeping it current, and human review only works if your systems put a person in the loop at the right step. Our guides to human-in-the-loop design, AI agent evaluation metrics and the AI agent security framework cover how to build sections 5 and 7 into real systems.

And it is not legal advice. Gigabit is an engineering firm. Have your counsel review the policy, decide which systems fall into which legal category, and adjust the wording for your jurisdiction.

When you need more than a policy

For a company that uses a handful of approved tools and builds no AI into its products, a well-kept version of this template is enough.

It stops being enough when teams have shipped AI agents that take actions, when a customer questionnaire or an auditor asks for evidence, or when you sell into the EU or regulated buyers. Our AI governance service inventories every AI system you build and buy, tiers each one against NIST AI RMF, ISO/IEC 42001 and, where counsel says it applies, the EU AI Act, then builds the controls the policy promises into the systems: human review steps, eval gates, logging, vendor checks and an incident runbook. The diagnostic is the AI Transformation Sprint, $25,000 fixed over 2 weeks, which ends in a working pilot of the first control. The build that follows is a fixed price in writing after scoping, and ongoing monitoring runs on Managed AI Operations at $3,000–$20,000 a month. If you need an agent or LLM feature tested for prompt injection and data leakage, the AI Security Assessment starts at $12,000 fixed. We build and document controls; we do not certify, audit for compliance or give legal opinions.