How to Create an AI Use Policy for Employees?

An AI policy template gives your organization a starting point for setting those rules. It explains which tools employees can use, what information they may share, how to review AI-generated output and who to contact when something goes wrong. This guide includes a practical framework you can adapt to your organization.

What is an AI use policy?

An AI use policy is an internal document that explains how employees may use artificial intelligence for work. It can cover generative AI tools, AI features built into business software and agents connected to company data or systems. When agents can access information or take action, the policy should also address AI agent governance.

A policy should not simply ban experimentation. It should help employees answer three practical questions: Can I use this tool? Can I share this information with it? Who needs to review the result?

A policy is one part of responsible AI adoption. It does not replace tool assessments, access controls, privacy reviews or employee training.

What should an AI policy include?

A useful AI policy tells employees what to do in specific situations. “Use AI responsibly” is too vague to guide someone who wants to summarize a customer proposal or draft a response with an AI assistant.

Define approved tools and use cases

List approved tools in a location employees can find. Name the person or team responsible for keeping that list current, and explain how to request approval for a new tool or an AI feature added to an existing product.

Be specific about use cases. For example, employees might be allowed to use an approved assistant to rewrite public-facing text, but need additional review before using AI to analyze a customer file. If employees are already using unapproved tools, Swiftask’s guide to Shadow AI in the workplace offers context for identifying those uses.

Classify data before setting restrictions

The data involved and the tool’s protections should shape the rule. A public announcement, an internal sales document and a confidential contract do not carry the same risks. A policy should distinguish between them rather than apply one blanket rule to every tool.

A practical classification might cover:

• Public information: material already approved for public sharing.

• Internal information: non-public information that may only be used with approved tools and for approved tasks.

• Personal data: information relating to an identified or identifiable individual. It should only be processed with AI tools approved for the relevant data and purpose and in accordance with applicable privacy requirements.

• Confidential information: trade secrets, credentials, privileged documents, sensitive business information or other protected data that should only be used when the tool and use case have been explicitly approved.

• Restricted information: secrets or highly sensitive data that must not be entered into tools unless they have been explicitly approved for that purpose.

Ask your privacy and security teams to help define these categories. Your organization’s rules should reflect the data, systems and contractual requirements involved. Swiftask’s Data Processing Agreement details the technical and organizational measures implemented to protect personal data, including access controls, encryption, monitoring and security governance. Organizations can assess these safeguards alongside their internal AI policies.

Set expectations for human review

AI-generated output should be checked before it is shared or used to make a decision. Define who checks factual accuracy, sources, tone and completeness, and what types of content require a second approval.

The level of review should match the potential consequences. A first draft of a public blog post is different from a customer response that creates a contractual commitment. For an AI agent connected to a business system, specify separately what it may read, prepare and execute. The review process should match its permissions.

AI policy template for employees

Use this sample as a starting point, not as a legally approved policy. Replace the bracketed text and have the relevant teams review it for your organization, tools and jurisdictions.

1. Purpose and scope: “This policy sets out how [organization] employees and other covered individuals may use AI tools and agents for work. It supplements other applicable company policies.”
2. Approved tools and access: “The list of approved AI tools is available at [location]. Before using a tool or AI feature that is not listed, employees must request review from [team] using [process].”
3. Approved use cases: “Approved use cases are listed in [catalog]. For each use case, the organization identifies permitted data, authorized users and any required review before the output is shared or acted on.”
4. Data and information: “Employees may only share information with an AI tool when they are authorized to do so and the tool is approved for that data and purpose. If unsure, stop and contact [privacy, security or other contact] before submitting the information.”
5. AI-generated output and decisions: “Employees must review AI-generated content for accuracy and relevance before using it. The following actions require approval from [role or team]: [list actions relevant to your organization].”
6. AI agents and system connections: “Each AI agent connected to a business system must have a defined purpose and an accountable owner. Its data access and permitted actions must be documented in [register or process]. New connections or execution permissions require review.”
7. Training and updates: “[Team] is responsible for explaining this policy and maintaining the approved-tool list. The policy is reviewed when tools, data, workflows or applicable requirements change.”

The template needs to match your organization’s actual tools and processes. Approval of a tool does not automatically approve every use of that tool.

How to put an AI policy into practice?

A policy works when employees can apply its rules without guessing. Publishing the document is only one step.

1. Inventory current use. Ask teams which tools they use, for what tasks and with what information. Treat the inventory as a way to understand work, not as a hunt for rule-breakers.
2. Review higher-risk use cases. Involve the teams responsible for IT, security, privacy, HR and legal review as appropriate.
3. Test the policy against real tasks. Try examples such as summarizing a meeting, reviewing a proposal or drafting a customer response. Employees should be able to identify the right tool and approval path.
4. Train employees. Explain the limits of AI-generated answers, the data rules and how to report a concern. If your organization is subject to the EU AI Act, Article 4 requires providers and deployers of AI systems to take measures to support the development of AI literacy among staff and other persons dealing with those systems on their behalf.
5. Align technical access with the policy. If only certain teams may use an agent or model, check that the permissions reflect that decision. Swiftask’s AI governance page describes workspace controls such as roles, permissions and usage monitoring.
6. Review and update. Revisit the policy when employees raise recurring questions, an incident occurs or the organization changes its tools and workflows.

In short: inventory, decide, explain, configure and review. If employees cannot tell what a rule means in practice, clarify it.

Make the policy operational

An effective AI policy gives employees clear answers about which tools they can use, what information they can share and what needs human review. It becomes more useful when training and technical permissions support the same rules.

If your team is defining those rules for AI agents and business tools, explore Swiftask’s AI governance controls.