AI Data Handling Policy Template for Businesses

An AI data handling policy should name approved tools, classify what employees may enter, prohibit sensitive data in unapproved systems, define access and retention, require human review for consequential work, and provide a path for reporting mistakes. The template below is a starting point for operational discussion, not legal advice. Adapt it to your contracts, industry obligations, security program, and applicable law with qualified reviewers before adoption.

1. Purpose and scope

[Company] permits approved AI systems when they support authorized business work and comply with this policy. This policy applies to employees, contractors, temporary workers, and any other person using company information, accounts, devices, or systems with an AI tool.

2. Approved tools and accounts

Users may access AI only through tools and accounts approved by [security or IT owner]. Personal accounts, browser extensions, meeting bots, and unsanctioned applications may not receive company information. The approved-tool register should record the owner, permitted uses, data controls, retention setting, access method, and review date for each system.

3. Data rules

• Public data may be used in approved tools for approved work.
• Internal data may be used only when the tool and use case are approved for that classification.
• Confidential, regulated, privileged, customer, employee, authentication, financial, health, or contract-restricted data may not enter an AI system unless the specific environment and workflow have written approval.
• Users must minimize inputs and remove identifiers when the work does not require them.
• Passwords, private keys, access tokens, and other secrets must never be submitted to a conversational AI interface.

4. Output review and prohibited decisions

A qualified person must review AI output for accuracy, source support, confidentiality, bias, and fitness before the output is relied on or shared. AI may not make an unsupervised decision about employment, credit, eligibility, legal rights, safety, medical matters, or another consequential outcome. Users remain accountable for the work they submit under their name.

5. Access, retention, and monitoring

Access follows least privilege and is removed when a role changes or ends. [System owner] documents retention, deletion, logging, vendor use, and model-training controls for every approved environment. Company administrators may monitor AI use on company systems according to published company policy and applicable law.

6. Incident reporting

Anyone who submits restricted information, receives harmful or suspicious output, discovers unauthorized access, or sees an AI tool behave outside its approved purpose must stop the workflow and report it to [security contact] through [reporting channel]. Reports should identify the tool, account, information involved, time, recipients, and any action already taken.

7. Ownership and review cycle

[Policy owner] maintains this policy, the approved-tool register, training, exceptions, and review records. Review the policy when tools, contracts, regulations, or business use cases change, and on the regular schedule established by the company. Record approvals and exceptions in writing.

Implementation checklist

• Inventory the AI tools already in use before announcing the policy.
• Create a short approved-tool register employees can actually find.
• Map the policy to the company's existing data classifications and incident process.
• Configure technical controls so the written rules are not the only defense.
• Train with real examples from each team and provide a safe way to ask questions.
• Review exceptions and incidents to improve both the policy and the approved environment.