How to Create an AI Acceptable Use Policy: A Practical Guide for Organizations
An AI acceptable use policy gives employees clear guardrails for using generative AI while helping your organization protect sensitive information, reduce risk and establish accountability.
An AI acceptable use policy is a set of organizational rules that defines how employees may use artificial intelligence tools for work. It typically explains which tools and use cases are permitted, what data may be shared, when human review is required, who approves new AI uses and how risks or incidents should be reported.
AI Use Is Already Happening—Whether Your Policy Is Ready or Not
Generative AI can improve productivity, accelerate research, help employees draft content and support new ways of working. But when employees begin using AI tools without clear guidance, organizations can create avoidable risks around confidential data, privacy, security, intellectual property, accuracy and accountability.
An acceptable use policy creates a practical starting point. It does not need to stop innovation. Its purpose is to make expectations clear so employees understand where AI can be used, where additional review is needed and what types of use should be avoided.
An AI acceptable use policy is one component of a broader AI governance program. Policy alone does not replace risk assessment, oversight, monitoring, security controls, training or ongoing governance.
12 Elements to Consider in an AI Acceptable Use Policy
The right policy will vary by organization, industry, risk profile and use case. These elements provide a practical framework for building a policy that employees can understand and apply.
1. Purpose and Scope
Explain why the policy exists, who it applies to and which AI technologies or services are covered.
2. Approved AI Tools
Define which AI tools employees may use and how new tools are reviewed and approved.
3. Acceptable Business Uses
Give examples of appropriate uses such as drafting, research assistance, brainstorming or summarization.
4. Prohibited or Restricted Uses
Identify activities that are not allowed or that require additional approval because of elevated risk.
5. Data Handling Rules
Clarify what confidential, personal, regulated or proprietary information employees may not enter into AI tools.
6. Human Review
Require appropriate human review before AI-generated content, recommendations or decisions are relied upon.
7. Accuracy and Verification
Make clear that AI output may be incomplete or incorrect and should be verified before business use.
8. Intellectual Property
Address organizational expectations around copyrighted material, proprietary content and generated output.
9. Security Requirements
Connect AI usage to existing cybersecurity requirements, access controls and approved technology practices.
10. Approval and Escalation
Define who employees should contact when they want to introduce a new AI tool or higher-risk use case.
11. Incident Reporting
Explain how employees should report accidental disclosure, inappropriate output or other AI-related concerns.
12. Training and Review
Establish expectations for employee education and periodic review as AI technologies and organizational needs change.
How to Create an AI Acceptable Use Policy in 7 Steps
A good policy should reflect how your organization actually uses AI. The process below helps connect policy development to real business activity and risk.
Inventory Current AI Use
Identify which AI tools employees are already using, where AI is embedded in existing applications and which departments are experimenting with new use cases.
Assess the Risk
Consider the data involved, business impact, security requirements, affected stakeholders and potential consequences if an AI tool or output fails.
Define Approved and Restricted Uses
Create clear examples of what employees may do, what requires additional approval and what should not be done with AI.
Establish Data Guardrails
Define rules for confidential, personal, regulated and proprietary information and align them with your existing data-handling and security policies.
Assign Ownership and Approval
Identify who owns the policy, who approves new tools or use cases and how IT, security, legal, compliance and business leaders participate.
Educate Employees
Explain not only what the rules are, but why they exist. Training should include practical examples employees will encounter in everyday work.
Review and Update the Policy
Revisit the policy as AI tools, organizational use cases, threats, regulations and business priorities evolve.
Sample AI Acceptable Use Policy Outline
The following is a starting framework—not a complete legal, regulatory or compliance policy. Organizations should adapt it to their own technology, risk profile, contractual obligations and regulatory requirements.
- Purpose: Define responsible and secure use of AI technologies.
- Scope: Identify employees, contractors, systems and AI tools covered.
- Approved Tools: Require employees to use organization-approved AI platforms.
- Data Protection: Prohibit entering restricted information unless specifically approved and protected.
- Human Oversight: Require review of AI-generated content and recommendations before material business use.
- Accuracy: Require verification of factual claims and outputs when accuracy matters.
- Security: Follow existing cybersecurity, identity, access and data-handling policies.
- Transparency: Require disclosure of AI use when organizational policy or the use case calls for it.
- Approval: Route new tools and higher-risk use cases through the designated review process.
- Incident Reporting: Report suspected data exposure, harmful output or unauthorized AI use.
- Training: Complete required AI awareness and governance training.
- Review: Update the policy periodically as technology and risk change.
How an AI Acceptable Use Policy Fits Into AI Governance
A policy tells employees what is expected. Governance creates the broader operating model that determines how AI is evaluated, approved, monitored and managed over time. Organizations may also need an AI inventory, risk assessments, defined accountability, security controls, monitoring, incident-response processes and ongoing program review.
NIST's AI Risk Management Framework organizes AI risk-management activities around four functions—Govern, Map, Measure and Manage—and emphasizes that AI risk management should be continuous across the AI lifecycle.
CCS helps organizations move from one-off AI rules to a structured governance program that connects policy, oversight, security, risk management and accountability.
Explore AI Governance Services →Frequently Asked Questions
What is an AI acceptable use policy?
An AI acceptable use policy defines how employees may use AI tools for work, including approved tools, acceptable uses, data-handling rules, human-review requirements, approval processes and incident reporting.
Does every organization need an AI acceptable use policy?
Organizations using or allowing employees to use AI should consider establishing clear rules for responsible use. The appropriate policy will depend on the organization's use cases, data, industry, risk profile and existing governance requirements.
What information should employees avoid putting into generative AI tools?
Organizations should define their own restrictions, but sensitive categories can include confidential business information, personal data, regulated information, customer data, credentials, proprietary material and other information that organizational policy does not permit employees to share with an AI service.
Who should own an organization's AI policy?
Ownership varies by organization. AI governance commonly requires coordination among business leadership, IT, cybersecurity, legal, privacy, compliance, risk and other stakeholders rather than relying on one department alone.
How often should an AI acceptable use policy be reviewed?
The policy should be reviewed periodically and when material changes occur in AI tools, organizational use cases, security threats, regulatory obligations, data practices or business requirements.
Is an AI acceptable use policy the same as AI governance?
No. An acceptable use policy is one component of AI governance. A broader governance program can also include AI inventories, risk assessments, approval workflows, roles and responsibilities, monitoring, security controls, incident response and ongoing oversight.
What is shadow AI?
Shadow AI generally refers to AI tools or services being used without formal organizational approval, visibility or oversight. An acceptable use policy can help reduce ambiguity, but organizations also need processes to identify and manage AI use.
Can CCS help develop an AI acceptable use policy?
CCS can help organizations establish AI policies and governance structures as part of a broader AI governance and risk-management program, including assessment, oversight, controls, implementation and ongoing governance support.
Need Help Turning AI Policy Into an AI Governance Program?
CCS can help you assess current AI use, establish policy and oversight, identify risk and build a governance approach that can evolve as AI adoption grows.