Generative AI Tool Approval Policy
Generative AI Tool Approval Policy template for reviewing employee AI use by risk, data class, and business need. It gives HR and IT a ready structure for approvals, renewals, guardrails, and discipline.
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Overview
This Generative AI Tool Approval Policy template sets out how employees request, use, renew, and lose approval for generative AI tools. It is designed for organizations that want a documented process for deciding whether a tool is allowed, what data it can touch, who reviews the request, and when approval must be revisited.
Use this template when employees are experimenting with public AI tools, when departments want to pilot an enterprise AI platform, or when leadership needs a consistent way to separate low-risk drafting from higher-risk uses involving confidential, personal, or regulated information. It is especially useful for HR, recruiting, legal, finance, customer support, and operations teams where AI output can affect employee rights, customer communications, or records handling.
Do not use this policy as a substitute for a broader security, privacy, or records-retention program. It is also not the right tool for banning all AI use outright; if the organization has no approved use cases yet, this template still helps define the review path and the conditions for exceptions. The structure is built to support approvals, renewals, prohibited uses, data handling rules, and discipline, so the reader can move from request to decision without guessing what happens next.
Standards & compliance context
- The policy should preserve employee rights under NLRA Section 7 by avoiding restrictions that could chill concerted activity or protected workplace discussions.
- Where AI is used in hiring, discipline, promotion, or accommodation workflows, the policy should support Title VII, ADA, ADEA, and EEOC-aligned review for bias, reasonable accommodation, and individualized assessment.
- If employee timekeeping, scheduling, or classification decisions are affected, the policy should not override FLSA obligations or create off-the-clock work expectations.
- If the tool is used in leave, accommodation, or medical-related workflows, the policy should preserve FMLA and ADA confidentiality and the interactive process.
- State-specific privacy and whistleblower rules may require additional carve-outs, including California privacy obligations and New York whistleblower protections where applicable.
General regulatory context for orientation only — verify current requirements with counsel or the relevant agency before relying on this template for compliance.
What's inside this template
Purpose
Explains why the policy exists and what risk it is meant to control.
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This policy establishes a controlled process for evaluating, approving, renewing, and revoking employee use of generative AI tools. The policy is designed to: - support legitimate business needs; - protect confidential, personal, and regulated data; - reduce legal, operational, and security risk; - help ensure compliance with employment laws, including **Title VII**, the **ADA**, the **FLSA**, the **FMLA**, and the **NLRA**; and - define when employees may use generative AI tools for work-related tasks. This policy is not intended to restrict lawful protected activity, including concerted activity protected by **NLRA Section 7**.
Scope
Defines which workers, tools, and business activities the policy applies to.
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This policy applies to all employees, contractors, interns, temporary workers, and managers who access or use generative AI tools for company business. It applies to: - company-provided AI tools; - third-party AI services used for work; - browser extensions, plugins, copilots, and embedded AI features; - AI features in productivity, recruiting, HR, finance, sales, and customer support systems; and - any employee use of generative AI that involves company data, customer data, employee data, or work product. **California employees:** use of personal data must comply with the **California Consumer Privacy Act (CCPA)** and any applicable California privacy notices. **EU/EEA users:** processing of personal data must comply with the **GDPR** and company-approved data transfer controls.
Definitions
Clarifies key terms like generative AI, approved tool, confidential data, and exception.
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**Generative AI tool**: A system that creates text, images, code, audio, video, or other content in response to prompts. **Approved tool**: A generative AI tool that has completed company review and has been authorized for a defined use case. **Data classification**: The company’s labeling of information by sensitivity, such as public, internal, confidential, restricted, or regulated. **Business need**: A documented operational reason for using a tool, including expected productivity, quality, customer service, or compliance benefits. **Human review**: Review by a qualified employee before work product is relied upon, published, submitted, or used in decision-making. **Restricted data**: Data that may not be entered into a generative AI tool unless explicitly approved by Legal, Privacy, and Information Security. **Interactive process**: The good-faith process used to evaluate a request for reasonable accommodation under the **ADA**.
Policy Statement
States the organization’s core rule for when AI tools may be used and under what conditions.
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Employees may use generative AI tools only when all of the following are true: 1. The tool has been approved for the intended use case. 2. The use is supported by a documented business need. 3. The data to be entered is permitted under the applicable data classification rules. 4. Required training has been completed. 5. A human review is performed where required. 6. The use does not violate law, contract, confidentiality obligations, or other company policies. Approval is limited to the specific tool, use case, user group, and data category reviewed. Approval for one use does not authorize broader use. The company may deny, limit, suspend, or revoke approval at any time based on risk, misuse, legal requirements, vendor changes, security concerns, or changes in business need.
Approval and Renewal Procedure
Shows the exact steps for requesting, reviewing, approving, renewing, or revoking use.
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### 1. Request submission Employees or managers must submit a request describing: - the tool name and vendor; - the business purpose; - the data classification involved; - the expected users and volume of use; - whether the tool will be used for HR, recruiting, compensation, scheduling, performance, or other employment-related decisions; - whether the tool will access personal data, confidential data, or regulated data; and - any known vendor terms, retention settings, or training data use settings. ### 2. Review The request must be reviewed by the appropriate approvers based on risk: - **Manager**: confirms business need; - **IT / Security**: reviews access controls, logging, retention, and security posture; - **Privacy / Legal**: reviews data handling, vendor terms, and legal risk; - **HR**: reviews employment-law implications when the tool may affect hiring, discipline, scheduling, pay, leave, accommodation, or performance management. ### 3. Approval criteria Approval may be granted only if the review confirms: - the tool is fit for the intended use; - the vendor terms are acceptable; - the data classification is compatible with the tool’s controls; - the use will not create unacceptable discrimination, wage-and-hour, privacy, or security risk; and - required safeguards are in place. ### 4. Renewal Approvals must be renewed at least every 12 months, and sooner if: - the vendor changes material terms, model behavior, or data use practices; - the business purpose changes; - the data classification changes; - a security incident or complaint occurs; or - Legal, HR, or Security determines re-review is needed. ### 5. Revocation Approval may be revoked immediately if the tool is misused, if the vendor no longer meets requirements, if the use creates legal or security risk, or if the company determines the use is no longer necessary.
Permitted and Prohibited Uses
Separates acceptable AI use from uses that require extra review or are not allowed.
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### Permitted uses Approved users may use generative AI tools to: - draft internal communications; - summarize non-confidential documents; - brainstorm ideas; - create first drafts of low-risk content; - assist with coding or analysis subject to review; and - support routine administrative tasks. ### Prohibited uses Unless specifically approved in writing, employees must not: - enter confidential, restricted, personal, employee, customer, payment, health, or other regulated data into an unapproved tool; - use AI output as the sole basis for employment decisions; - rely on AI-generated content without human review where accuracy or legal compliance matters; - use AI to create discriminatory, harassing, deceptive, or retaliatory content; - use AI to circumvent wage-and-hour, leave, accommodation, or recordkeeping obligations; - submit company information to a public model that trains on prompts or outputs unless approved; - claim AI-generated work as verified fact without checking it; or - use AI in a way that interferes with protected employee rights under the **NLRA**.
Data Classification and Handling Rules
Tells employees what data can be entered, stored, shared, or exported from an AI tool.
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Employees must follow the company’s data classification rules before entering any information into a generative AI tool. - **Public data**: may be used in approved tools. - **Internal data**: may be used only in approved tools with appropriate safeguards. - **Confidential data**: may be used only if the tool and use case are specifically approved by Legal, Privacy, and Security. - **Restricted or regulated data**: may not be entered unless there is explicit written approval and documented controls. Examples of restricted or regulated data include: - Social Security numbers; - bank account numbers; - payment card data; - health information; - immigration records; - background check results; - accommodation requests; - leave records; - compensation data; - disciplinary records; and - protected employee demographic data. Employees must minimize data use, redact where possible, and avoid entering unnecessary personal information.
Employment Law and HR Safeguards
Builds in protections for hiring, discipline, leave, accommodation, and employee rights.
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When generative AI is used in connection with hiring, promotion, scheduling, discipline, performance management, leave, accommodation, or compensation, the following safeguards apply: - A qualified human reviewer must make the final decision. - The tool may not be used in a way that causes disparate treatment or disparate impact on protected classes under **Title VII** or other anti-discrimination laws. - The company must evaluate whether the tool affects exempt/non-exempt classification, overtime, or timekeeping under the **FLSA**. - The company must not use AI to deny or interfere with rights under the **FMLA**. - Requests for accommodation must be handled through the ADA **interactive process**. - Employees may raise concerns about AI-related workplace issues without retaliation. Any manager using AI for employment-related decisions must consult HR before implementation.
Roles & Responsibilities
Assigns ownership so employees know who approves, who monitors, and who escalates issues.
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- **Employees**: use only approved tools, follow data rules, verify output, and report errors or incidents. - **Managers**: document business need, ensure team compliance, and escalate requests involving higher-risk use cases. - **HR**: review employment-law impacts, oversee training for people-related use cases, and coordinate accommodation or complaint handling. - **IT / Security**: assess vendor security, access controls, logging, retention, and incident response requirements. - **Privacy / Legal**: review data processing, vendor terms, cross-border transfers, and regulatory obligations. - **Procurement**: ensure vendor review and contract terms are completed before purchase or renewal. - **Policy holder**: maintain the policy, coordinate annual review, and approve exceptions where authorized.
Compliance, Monitoring, and Discipline
Describes how violations are detected, documented, corrected, and disciplined.
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The company may monitor the use of approved AI tools to the extent permitted by law and company policy. Violations of this policy may result in corrective action up to and including revocation of access, documented warning, performance improvement plan (PIP), suspension, or termination, depending on the severity of the violation and applicable law. The company will apply this policy consistently and in a manner that does not interfere with protected activity, including lawful concerted activity under the **NLRA**. Employees must promptly report suspected misuse, inaccurate outputs that affect business decisions, privacy incidents, security incidents, or vendor concerns.
Exceptions
Creates a controlled path for temporary deviations from the standard rule.
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Any exception to this policy must be approved in writing by Legal, HR, and Security, or by another designated policy holder, before the exception is used. Exceptions must specify: - the business justification; - the data allowed; - the duration of the exception; - compensating controls; and - the review date. Temporary exceptions should be narrowly tailored and time-limited.
Review & Revision
Sets the review cadence and triggers for updating the policy as tools and laws change.
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This policy will be reviewed at least annually and updated as needed to reflect changes in law, vendor practices, business operations, or risk profile. The policy holder is responsible for maintaining the current version, documenting revisions, and ensuring that approvals are revalidated when material changes occur.
How to use this template
- 1. Fill in the effective_date, version, review_frequency, applicable_jurisdictions, applicable_roles, and policy holder before publishing the policy.
- 2. Define the approval workflow in the Approval and Renewal Procedure section, including who reviews business need, data risk, legal exposure, and final signoff.
- 3. List the permitted and prohibited uses by department or risk tier, and tie each one to the data classification and handling rules.
- 4. Assign employees, managers, HR, IT, Security, and Legal their specific responsibilities so requests, renewals, and exceptions do not stall.
- 5. Publish the monitoring, discipline, and exception process together so employees know what happens after a violation, a complaint, or a change in tool risk.
- 6. Review the policy annually and after major vendor, regulatory, or internal process changes, then update training and intake forms to match.
Best practices
- Require a documented business need for every approval so the policy does not become a blanket permission slip.
- Classify data before tool use, and prohibit entry of confidential employee, customer, or legal information unless the tool has been explicitly approved for that class.
- Separate low-risk drafting use from high-risk decision support, especially where HR, hiring, discipline, or pay decisions are involved.
- Require human review of all AI-generated content before it is sent externally or used in employment decisions.
- Keep a renewal date on every approval and revoke access automatically if the approval expires.
- Document exceptions in writing with a time limit, a named approver, and a clear reason for the deviation.
- Train managers not to approve tools informally in chat or email, because undocumented approvals are hard to audit and easy to misapply.
What this template typically catches
Issues teams running this template most often surface in practice:
Common use cases
Frequently asked questions
What does this Generative AI Tool Approval Policy cover?
It covers how employees request, use, renew, and lose approval for generative AI tools at work. The template is built around business need, data classification, and risk review, so it fits both self-service tools and approved enterprise platforms. It also includes HR safeguards for employee data, protected activity, and disciplinary follow-up when someone uses a tool outside policy.
Who should run the approval and renewal process?
HR, IT, Security, Legal, or Privacy typically share ownership, with one policy holder named as the final approver. In smaller organizations, a single cross-functional reviewer can handle intake and renewal, but the workflow should still separate business justification from data-risk review. The template is designed so you can assign clear roles without creating a bottleneck.
How often should approvals be renewed?
Annual review is the standard cadence, with faster review if the tool changes, the vendor changes terms, or the employee’s use case expands. Renewal should confirm the tool is still needed, the data classification is still accurate, and any required training or controls are still in place. This template includes a renewal step so approvals do not become permanent by accident.
What laws or compliance areas does this policy need to consider?
The policy should align with FLSA, FMLA, ADA, Title VII, ADEA, EEOC guidance, and NLRA protections where employee use or monitoring could affect workplace rights. It should also account for state-specific overlays such as California privacy rules, New York whistleblower protections, and other local data or leave requirements where applicable. If the policy touches employee data, it should also address GDPR or CCPA-style handling rules where relevant.
What are the most common mistakes this template helps prevent?
Common failures include allowing unapproved tools to process confidential data, skipping renewal, and approving use without documenting the business need. Another frequent gap is treating all AI output as reliable without human review, especially for HR, legal, or customer-facing content. The template also helps prevent inconsistent approvals that can create fairness or discrimination concerns.
Can we customize this policy for different teams or risk levels?
Yes. You can set different approval paths for low-risk drafting tools, higher-risk tools that touch employee or customer data, and restricted uses that require legal or security signoff. Many organizations also customize the permitted and prohibited uses section by function, such as HR, recruiting, finance, or customer support. The template is structured so those carve-outs stay visible instead of buried in email.
How does this policy compare with ad hoc manager approval?
Ad hoc approval is hard to audit, easy to forget, and often inconsistent across departments. This template creates a documented process with defined criteria, renewal timing, and escalation points, which makes approvals easier to defend and easier to revoke when needed. It also gives employees a clear path for asking before they use a tool.
What should we connect this policy to in practice?
It should connect to your acceptable use policy, information security policy, privacy notice, records retention rules, and any HR policies on confidentiality or workplace conduct. If you use an intake form, ticketing system, or vendor review workflow, this template can point employees to those steps. That makes the policy actionable instead of just descriptive.
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