AI Use Policy Template + Variable Legend

Jan 7, 2026

Organizations are adopting AI tools quickly—often faster than their governance and risk controls can keep up. AI can boost productivity, but it can also create exposure related to confidentiality, security, privacy, accuracy, and intellectual property.

That’s why many organizations are now formalizing expectations through an AI Use Policy: a practical document that defines what AI can be used for, what it must never be used for, and how the organization protects data and people when AI is involved.

This article explains what the AI Use Policy template covers, how to implement it, and exactly what information your organization needs to complete the placeholders.

What the AI Use Policy Covers

Document Control (New in the updated template)

At the top of the template, there is a simple Document Control block to support auditing and internal governance. This records:

When the policy became effective
The current version
Who approved it
Who owns it (accountable leader)

This small addition helps significantly with compliance, internal accountability, and change management.

1) Purpose

This section sets the tone: AI is permitted to support work, but it must be used in a way that protects the organization, clients, and employees. It establishes core principles like confidentiality, security, accuracy, fairness, accountability, and transparency.

2) Scope

The scope clarifies who the policy applies to (employees, contractors, vendors, or all) and makes clear it applies regardless of where the work is performed or what device is used.\

3) Definitions

Definitions reduce ambiguity and support consistent enforcement—especially important for non-technical staff. The policy defines key concepts like AI, generative AI, and sensitive/confidential data.

4) Approved Use of AI

This section describes permitted use cases (drafting, summarization, ideation, research support, etc.) while emphasizing a non-negotiable rule: AI output must be reviewed by a human before being used.

5) Prohibited Use of AI

The prohibited use section is where the policy prevents the highest-risk outcomes. Common prohibitions include:

Using AI for automated decisions affecting individuals (without proper oversight)
Entering regulated or sensitive information into AI tools
Using AI to bypass security controls, generate harmful code, or support unauthorized activity

6) Approved AI Tools and Services

This prevents “shadow AI” by clarifying which platforms are approved for business use and how new tools must be reviewed and authorized before adoption.

7) Data Protection and Privacy

This is the section most organizations care about most. It restricts what data can be entered into AI tools, sets expectations around anonymization/redaction when appropriate, and requires compliance with applicable regulations and contracts.

8) Accuracy, Bias, and Human Oversight

AI can be wrong, incomplete, or biased. This section reinforces that AI is not an authority and must be validated—especially for high-impact communications, client-facing output, or decisions affecting people.

9) Intellectual Property

This section reduces IP and licensing risk by requiring review for originality and by clarifying that AI-assisted work product created for the organization remains the organization’s property.

10) Training Requirements

Training operationalizes the policy. It sets the expectation that staff must complete training before using AI tools and complete refreshers periodically.

11) Violations and Enforcement

A policy is only useful if it can be enforced. This section defines:

How to report violations or concerns
Consequences for misuse (often referencing an existing disciplinary policy)

12) Policy Review and Updates

AI changes quickly. This section assigns ownership and establishes a review cadence so the policy stays current.

Variable Legend: All Placeholders Used in the Template

Use the following list to complete the template quickly and consistently:

Document control

[Effective Date] – When this policy becomes active
[Version] – Your internal document version (e.g., 1.0, 1.1)
[Approval Authority / Approved By] – Executive/committee approving the policy
[Policy Owner Title] – Role responsible for maintaining the policy (e.g., CIO, CISO, Compliance Officer)

Organization and scope

[Organization Name] – Legal organization name
[Applies To] – Who is covered (employees, contractors, vendors, or all)

Tooling and approvals

[Approved AI Tools] – Approved tools/services (name them)
[AI Tool Approval Process] – How new tools are requested/approved (ticketing system, committee review, etc.)

Data and compliance

[Prohibited Data Types] – Data categories never allowed in AI prompts (e.g., PHI, PII, credentials, client confidential data)
[Applicable Regulations] – Regulations/standards/contractual obligations that apply (e.g., HIPAA, GLBA, GDPR, client contract terms)

Training

[Required Training Program] – Training course or method (LMS course name, internal module)
[Training Frequency] – How often refresher training occurs (e.g., annual)

Enforcement and governance

[Violation Reporting Method] – Where to report issues (e.g., manager, HR, compliance portal, security hotline)
[Disciplinary Policy Reference] – The policy/process that governs disciplinary action
[Policy Review Frequency] – How often policy is reviewed (e.g., annually)
[Next Review Date] – Next scheduled review date