An AI acceptable use policy template turns broad principles into rules people can apply before they open a tool, enter data, rely on output or connect a system. It should define approved purposes, prohibited behavior, data boundaries, verification, ownership, incident reporting and review.
Use the builder above to create a starting draft, then adapt it to the actual tools, roles, data, decisions and jurisdictions involved. A copied policy is not governance unless employees understand it, approved workflows support it and owners monitor whether it works.
1. Purpose of an AI acceptable use policy template
The purpose is to help people use AI consistently with organizational objectives, data rules, security controls, contractual duties and the rights of affected people. It should enable approved low-risk use while making boundaries visible.
State that AI output may be incomplete, inaccurate, biased, insecure or unsuitable for the intended context. Users remain responsible for following the approved workflow and escalating uncertainty. Do not promise that the policy makes a tool safe or compliant.
2. Define the scope precisely
List who the policy covers: employees, contractors, temporary staff, managers, developers or other users. Cover paid, free and trial tools, embedded AI features, browser extensions, APIs, models, meeting bots, agents and integrations used for organizational work.
Define the information classes that may and may not be entered. Address personal, confidential, customer, employee, regulated, credential, source-code and contract-restricted data. Link to the organization’s authoritative classification and retention rules instead of inventing a second taxonomy.
| Policy question | Weak wording | Operational wording |
|---|---|---|
| Tools | Use safe AI. | Use accounts and tools listed in the approved register. |
| Data | Do not share sensitive data. | Follow named data classifications and approved exceptions. |
| Review | Check the answer. | Apply the workflow’s documented quality and approval steps. |
| Incidents | Report problems. | Stop the affected action and use the named reporting channel. |
3. Assign roles and accountability
Name a policy owner responsible for approval, training, exceptions, monitoring and review. Tool owners maintain product, plan, integration and vendor information. Workflow owners define permitted tasks, quality thresholds and human review. Users follow the policy and report unexpected behavior.
Involve security, privacy, legal, HR, procurement, records, compliance and affected operational teams according to the use case. The NIST AI Risk Management Framework organizes work through Govern, Map, Measure and Manage, emphasizing context and shared responsibility rather than placing every decision on the end user.
4. Define permitted and prohibited uses
Permitted use should identify the task, approved tool, acceptable inputs, output review and destination. Examples may include brainstorming with non-sensitive information, summarizing approved material or preparing a first draft that receives qualified review.
Prohibit entering restricted data into unapproved services, bypassing access or safety controls, impersonation, unlawful or deceptive activity, undisclosed fabricated evidence, and consequential decisions without authorized human control. Avoid a closed list that implies everything unmentioned is allowed; require approval for new or materially changed use cases.
5. Connect policy statements to controls
- Use named accounts, appropriate authentication and minimum permissions.
- Verify material claims, calculations, citations and decisions against reliable evidence.
- Label or disclose AI assistance where the context, policy or law requires it.
- Keep records required for accountability without retaining unnecessary prompts or outputs.
- Prevent unapproved autonomous actions and monitor approved automation.
- Reassess when the model, plan, terms, integration, data or purpose changes.
Use the AI tool privacy and security checklist to translate general requirements into product- and plan-specific evidence.
Approve tools and integrations before use
Define a lightweight request path so employees do not have to choose between waiting indefinitely and using an unapproved service. The request should identify the tool and plan, intended workflow, users, data, integrations, output destination, owner and expected duration. Route higher-risk requests to the necessary specialists.
Approval should be limited to the documented use, not interpreted as permission for every advertised feature. Re-review new connectors, autonomous actions, different data or a move from individual to team deployment. Record rejection or conditional approval so the same issue is not repeatedly assessed without context.
Address intellectual property and external communication
Tell users how to handle copyrighted, licensed, confidential and trademarked material in inputs and outputs. Require verification of originality, attribution and usage rights appropriate to the publication or product. State when AI assistance must be disclosed and who may approve customer-facing, public or regulated communications.
6. Create an approval and exception record
Maintain an inventory of approved tools and use cases with owner, purpose, users, data, integrations, review, risk rating and renewal date. Record exceptions with scope, reason, compensating controls, approver and expiry. Permanent informal exceptions erode the policy.
The ICO’s guidance on AI accountability and governance discusses meaningful risk appetite, DPIAs and controller–processor relationships where personal data is involved. Adapt the policy to applicable requirements rather than treating a generic template as legal determination.
7. Train, monitor and review the policy
Training should use realistic examples and show both permitted and prohibited versions of a task. Explain how to verify output, protect data, recognize an incident and request approval. Confirm understanding for roles with elevated permissions or consequential use.
Review adoption, exceptions, incidents, shadow tools, unused subscriptions and provider changes. Set a scheduled review and event-based triggers. Coordinate changes with the AI risk assessment template and AI incident response plan.
8. Policy examples
Reviewed marketing draft
A team may use an approved tool with public product information to create a first draft. A named reviewer verifies claims, intellectual-property concerns, tone and required disclosures before publication.
Customer data in a free tool
The action is prohibited when the service and plan have not been approved for that data. Removing a customer’s name may not be enough if the remaining information can identify the person or remains contract-restricted.
Automated decision
A user may not connect an AI output directly to an employment, credit, eligibility or other consequential action merely because the tool offers automation. The use case needs specific assessment, authority, controls and human oversight.
Common policy mistakes
- Publishing vague principles without approved workflows.
- Covering only standalone chatbots and missing embedded AI or integrations.
- Using “sensitive” without linking to actual data classifications.
- Telling users to verify output without defining the required standard.
- Allowing exceptions without owner, expiry or evidence.
- Failing to provide a reporting channel and non-retaliatory escalation.
- Leaving the policy unchanged after material tool or provider changes.
AI acceptable use policy template FAQ
Is an AI policy legally required?
Requirements vary by organization, activity and jurisdiction. A policy can support governance and evidence, but it does not by itself determine or prove legal compliance.
Should a small business have an AI use policy?
A short policy is useful when people use AI for business work or data. Keep it proportional, name approved tools and make reporting and ownership clear.
How often should the policy be reviewed?
Use a scheduled review and update it after material changes to tools, models, terms, integrations, data, law, incidents or approved uses.
Can the generated draft be adopted unchanged?
No. It lacks the organization’s specific authority, tools, data rules, jurisdictions, contracts, reporting channels and approval process.
Methodology and limitations
ScoutChoice developed this AI acceptable use policy template from a use-case-led governance structure: purpose, scope, roles, permissions, controls, evidence, incidents and review. The builder creates text locally in the browser and does not transmit or store entries.
The guide is general information, not legal, employment, privacy, security or compliance advice. Obtain appropriate review and reconcile the final policy with applicable law, contracts, collective arrangements, internal policies and actual technical controls.