AI Acceptable Use Policy Template for IT Teams and MSPs, With Rules for AI Agents

Updated: November 2026. EU AI Act articles, the Commission's AI literacy Q&A, NIST AI 600-1, Microsoft Learn and survey figures checked against primary sources on 11 November 2026.

Somebody in finance pastes a client spreadsheet into a free chatbot, and nobody ever told them not to. Staff need a short list of approved tools, a clear line on which data goes where, and a person to ask. This AI acceptable use policy template gives IT teams and MSPs 12 copy-ready clauses, a data-by-tool table, rules for AI agents and the control behind each clause.

TL;DR

• What it is. A short staff policy naming approved AI tools, the data each may take, and who checks the output.
• Copy the template. Fill the brackets in 12 clauses, get an executive to sign, then collect acknowledgments.
• Data by tool. Credentials go into no AI tool, and client data only into tools approved for it.
• Agents get rules. Anything that sends, changes, deletes or runs scripts needs an owner, its own account and logs.
• Back each clause. Pair every rule with a control and evidence.

What Is an AI Acceptable Use Policy?

An AI acceptable use policy tells staff which AI tools they may use for work, what data each one can take, and what's never allowed. It sits beside your general acceptable use policy and is short enough for every employee to read and sign.

KPMG's Trust in AI study, released 29 April 2025, surveyed 1,019 people in the US. In it, 44% of US workers said they use AI at work without proper authorization or in ways that break policy. 46% had uploaded sensitive company information or IP to public AI platforms, and about half didn't know whether their use was allowed.

ISACA's 2026 AI Pulse Poll of more than 3,400 digital trust professionals, released 5 May 2026, found 38% of organizations have a formal, complete AI policy. That's up from 28% in 2025, by ISACA's own count, and 25% still have none.

The policy is the part of AI governance every employee reads. The registers and audits behind it stay with IT.

An r/ITManagers poster found finance running client data through AI tools IT had never heard of. The top reply calls it an HR and legal policy job, backed by education and approved tools.

How It Differs From Your General Acceptable Use Policy

Your general acceptable use policy covers devices, networks, email and passwords. It rarely mentions prompts, AI features inside approved apps, or tools that connect to a mailbox. Keep both, and add one line to the general policy that points to the AI one.

A policy says what staff may do, and a procedure says how to do one task, like requesting a new AI tool. Our guide to policy vs procedure shows where each piece lives.

Personal devices stay in your BYOD policy template. The AI policy decides which AI apps on them may touch work data.

In our AI governance framework, this policy is row GV-2. The IT lead owns it, an executive approves it, and signed acknowledgments are the evidence.

What an AI Acceptable Use Policy Covers

The template below has 12 clauses:

1. Purpose and scope.
2. Approved tools in two tiers.
3. Data rules, by data type and tool.
4. Work accounts through single sign-on.
5. Connecting AI to work systems.
6. AI agents and automation.
7. Checking output.
8. Disclosure and intellectual property.
9. Prohibited uses.
10. New tools and exceptions.
11. Reporting incidents, without blame.
12. Training, acknowledgment and review.

Tenable, a security vendor, explains what an AI acceptable use policy is in under three minutes on its own channel. Its chapters run from data classification and approved tools to accountability and monitoring.

The AI Acceptable Use Policy Template

Copy the text below, fill every [bracket], and have counsel review it before rollout. It's a starting point, not legal advice.

The One-Page Staff Version

Give every employee this page and keep the full text on file.

Go ahead. Use Tier A tools on your work account, and Tier B tools for public data only.

Ask IT first. New AI tools, AI browser extensions, connecting AI to email or files, meeting note-takers, and anything that acts on its own.

Never. Passwords or keys in a prompt, client data in an unapproved tool, or AI deciding about people alone.

Check it. A person reviews AI output before customers or production see it.

Report it. Tell [IT contact] within [24 hours] if something goes wrong. No blame.

Scope and Tools

[Company] AI Acceptable Use Policy. Version [1.0], effective [date]. Owner: [IT lead]. Approved by: [executive name and title].

1. Purpose and scope. This policy covers every employee, contractor and [MSP technician] who uses AI for [Company] work. AI means any AI tool, AI feature inside an approved app, browser extension with AI, or agent that acts for you, on any device or account used for work.

2. Approved tools. IT keeps the approved AI tool list at [location]. Tier A tools are approved for internal data, and for client data where the list says so. Tier B tools are for public data only. Anything else needs a request under clause 10.

Data and Accounts

3. Data rules. Check the data-by-tool table before you paste, upload or connect anything. The data owner decides how data is classified, and if you're unsure, treat it as confidential. Never put passwords, API keys, tokens or recovery keys into any AI tool.

4. Accounts. Use your [Company] work account, signed in through [single sign-on provider]. Personal or free AI accounts are for public data only. Don't share AI accounts or their API keys.

Connectors and Agents

5. Connecting AI to work systems. Ask IT before you connect an AI tool to email, files, calendars, chat or any business system. That includes approving an app's request to read your mailbox, installing an AI browser extension, and adding a note-taker or meeting bot to a call. IT answers within [2 business days].

6. AI agents and automation. An agent is AI that acts: it sends messages, changes settings, deletes data or runs scripts. Every agent has a named owner, its own account with only the access it needs, and a log of its actions. Actions on the [approval list] wait for a person's yes, and no agent runs on a person's credentials.

Output, Disclosure and Prohibited Uses

7. Checking output. You're responsible for what you send, whoever or whatever wrote it. A person checks AI output before it reaches a customer, production or a decision about a person. AI-written code and scripts get the same review as any other code.

8. Disclosure and intellectual property. Label AI-generated content where customers or the public see it, following [content guide]. Chatbots and agents that talk to customers say they're AI. Don't upload material [Company] has no rights to use.

9. Prohibited uses. Never allowed: credentials or secrets in a prompt, client data in a tool not approved for it, and hiring, discipline or dismissal decisions without a person's review. Also banned: recognizing or inferring staff emotions, deepfakes or impersonation, and using AI to get around a security control.

Requests, Incidents and Review

10. New tools and exceptions. Request a new AI tool or use case at [request form], and IT answers within [5 business days]. An exception needs a named owner, a reason, sign-off from [IT lead] and an end date no more than [90 days] out.

11. Reporting incidents. Tell [IT contact] within [24 hours] if data went into the wrong tool, an agent did something it shouldn't, or hidden instructions seem to steer an AI tool. Reports are blame-free and go into the incident response plan.

12. Training, acknowledgment and review. Everyone completes AI training at onboarding and [every year]. You sign this policy when you join and at each major version. IT checks the approved tool list every [quarter] and reviews the full policy every [year], after any AI incident and when an approved vendor changes its terms.

I have read the [Company] AI Acceptable Use Policy, version [1.0], and I agree to follow it. Name: [ ]. Signature: [ ]. Date: [ ].

Which Data Goes Into Which AI Tool

This is the table clause 3 points to.

The data owner classifies the data, not whoever holds the prompt box. If nobody knows, treat it as confidential.

A free account sits outside your single sign-on, your logs and your vendor contract. That's how shadow IT starts, and why the last column is strict.

Rules for AI Agents, Connectors and Note-Takers

Clauses 5 and 6 exist because AI now acts as well as answers. A connector reads a mailbox, a note-taker joins every call, and an agent resets passwords. Our explainer on what agentic AI is covers how an agent differs from a chatbot.

In Microsoft 365, the Entra admin consent workflow is the control behind clause 5. When users can't consent to an app themselves, they send a request instead. It goes to designated reviewers by email, they approve or deny it, and the user is notified. A Global Administrator turns it on.

AI browser extensions are connectors too, so review their browser extension permissions before they reach the allowlist.

Which agent actions wait for a person is a design choice. Our human in the loop guide sets it per action, by blast radius and how hard the action is to undo.

Stopping an agent matters as much as approving one. In ISACA's 2026 poll, 56% didn't know how long halting an AI system after a security incident would take. Our agent sprawl guide covers counting the agents already installed.

A connector that reads email also reads whatever an attacker writes into one. That's prompt injection, and clause 11 asks staff to report it.

OpenFrame is open, AI-native infrastructure for IT and security: Fae resolves support requests and Mingo runs IT operations, and every click, script and reply, human or AI, lands in the audit log. It costs $1 per device per month, with a 14-day free trial. Flamingo builds OpenFrame, so hold its agents to clause 6 like any other.

The Control Behind Each Clause

A clause without a control is a request. Each row adds the control behind a clause and the evidence that it ran.

Our AI governance tools roundup sorts the products behind clauses 2 to 5 by the job they do.

For clause 3, DLP software can watch paste and upload into AI sites.

For clause 7, our guide to vibe coding risks covers what slips through when AI-written code skips review.

What the EU AI Act and NIST Expect

As of November 2026, Article 4 of the EU AI Act asks providers and deployers to take measures to support their staff's AI literacy. That covers others using AI on their behalf too. The measures should fit the staff's knowledge, the context of use and the people affected, with no set level of literacy required. That wording comes from the Digital Omnibus on AI, Regulation (EU) 2026/1744, in force since 27 July 2026.

Article 4 has applied since 2 February 2025. National authorities supervise and enforce it from 2 August 2026, per the Commission's AI literacy Q&A (updated 20 October 2026). No certificate is needed, and the Q&A says organizations can keep an internal record of training. A company whose staff use a tool like ChatGPT for ad copy or translation falls under Article 4.

So Article 4 doesn't demand a written policy, but clause 12's records fit what the Q&A describes.

Article 5(1)(f) has banned AI that infers the emotions of people at work since 2 February 2025, with medical and safety exceptions. Clause 9 repeats it. Article 50 has applied since 2 August 2026, and as of November 2026 it asks providers to make AI that talks to people identify itself. It also asks deployers to disclose deepfakes, and clause 8 reflects both.

NIST AI 600-1, the Generative AI Profile from July 2024, names acceptable use policies in three actions. GV-1.4-002 asks for transparent policies that address illegal use. GV-3.2-003 asks you to define them per AI interface and human-AI setup, including what the AI should refuse. GV-6.1-010 extends them to contractors and other third parties.

In our mapping, clauses 1 and 9 answer the first, clauses 2, 5 and 6 the second, and clause 1's contractor scope the third. NIST says AI RMF 1.0 is being revised, with no new version out as of 11 November 2026.

Rolling Out the Policy

ISACA's 2026 poll found 33% of organizations train all employees on AI. Make training and signatures one step:

1. Build the approved list first, so staff have somewhere to go on day one.
2. Fill the brackets and get the executive signature.
3. Train at onboarding and on a fixed cycle, and keep the records.
4. Collect acknowledgments at hire and at each major version.
5. Check the tool list quarterly, and review the full policy yearly, after vendor terms change, after an AI incident, and when a new kind of tool arrives.

Our guide to security awareness training covers making training stick past the first week.

Every exception gets one row in the log. Copy this one:

Clause 11 reports go into your incident response plan, with the AI tool, the data and the account noted on the ticket.

Running One Policy Across MSP Clients

An MSP needs two layers. Its own policy covers its techs, who work inside every client's tenant. Each client signs its own, with its own approved list, since one client may approve a tool another has banned.

Inside a client's data, that client's list wins. Client names and NDA details stay out of any tool not approved for that client.

Keep each client's list in its documentation, and add the policy to your MSP onboarding checklist so new clients sign in their first month.

A poster on r/msp asked whether their MSP's techs should use any AI tool or approved subscriptions only. The top reply says approved, paid tools only and no client names or NDA details. The tech verifies output and never sends it straight to a client.

Fill the Brackets, Then Sign It

An AI acceptable use policy works when staff can read it in five minutes and IT can prove each clause ran. Build the approved list, set the data-by-tool table, give agents owners and logs, and collect signatures. Check the tool list every quarter, and review the full policy once a year and after any vendor terms change. Read our AI governance framework next for the owners and review dates around this policy.