What Is an AI Policy?
An artificial intelligence (AI) policy establishes clear guidelines and standards for an organization’s use of artificial intelligence, protecting against legal risks, data leaks, bias, and employee misuse. It’s essential today, especially with AI’s spread in hiring, customer support, and content generation. Copyright issues are also evolving, such as ownership of AI-generated work under US law.
Legal & Regulatory Pressures
- The EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the California Privacy Rights Act (CPRA), the Health Insurance Portability and Accountability Act (HIPAA), and the EU AI Act all mandate privacy, fairness, and transparency.
- Copyright Office guidance: Only AI content with sufficient human creativity is eligible for copyright; AI-only content is not.
Depending on your organization’s region, these rules affect who’s responsible, what data can be processed, and when AI use must be disclosed.
Key Components of an Effective AI Policy
A strong AI policy helps organizations use AI safely, ethically, and legally. Based on our downloadable template, here are the core elements to include:
- Scope and Definitions: Specifies who the policy applies to and defines key terms like PII, AI-generated content, and high-impact decisions. Lists approved AI tools and the process for evaluating new ones.
- Purpose and Principles: Explains why the policy exists: to ensure ethical use, protect data, prevent misuse, and promote transparency and accountability.
- Acceptable Use: This section sets guidelines for proper AI use, prohibiting misuse, deceptive practices, or excessive automation. AI must support, not replace, human decision-making.
- Legal Compliance: AI use must comply with laws such as GDPR, CCPA, DMCA, and EEO. This includes data privacy, copyright, intellectual property (IP) rights, and discrimination laws.
- Transparency and Oversight: Requires users to log AI use, disclose AI-generated content, and verify outputs.
- Data Security and Confidentiality: Restricts the use of confidential or personal data in AI tools unless approved and secured. Consider pairing with a confidentiality agreement for added protection.
- Bias and Fairness: Requires regular review of outputs for bias or unfairness, and mandates reporting of any harmful results.
- Training and Awareness: Employees must complete training in AI ethics, privacy, tool use, and risk reporting.
- Third-Party Tools: External AI vendors must comply with legal standards, maintain security certifications, and agree to audits.
- Incident Response: Details steps for reporting tool failures, data breaches, or harmful outputs, including coordination with IT and root cause analysis.
- Risk Management: Classifies AI tools by risk level. High-risk tools require extra oversight, audits, and impact assessments.
- Cross-Border Use (Optional): Addresses compliance with international regulations and secure data transfers across jurisdictions.
- Governance & Enforcement: Outlines roles (e.g., AI officer), audit rights, enforcement actions, and policy update procedures.
How to Create an AI Policy
Establishing an AI policy is not only about compliance; it also prepares your organization for a future where artificial intelligence significantly impacts daily business operations. To create an effective AI policy, follow these steps:
1. Customize Template
Using Legal Templates’ free AI policy template, start by customizing to reflect your company’s name, industry, and internal structure. Fill in:
- The effective date
- The names of policy owners or committee members
- Your company’s list of approved AI tools
- Any department-specific guidelines or training requirements
Tailor sections that don’t apply to your organization and include any regional legal considerations.
2. Assign Ownership & Roles
Designate key personnel responsible for AI governance:
- AI Officer: Point of contact for tool approvals, incident reports, and compliance
- AI Governance Committee: A cross-functional team (e.g., HR, IT, legal) that reviews risks, vendor tools, and policy updates. Ensure responsibilities are clearly documented and understood.
3. Train Your Team
AI policies are only effective if users understand them. Training should include:
- Basic AI literacy – What AI is and isn’t
- Tool-specific training – How to use company-approved AI tools responsibly
- AI ethics and bias awareness
- Data privacy & security practices
- Incident reporting procedures
Track participation and require periodic refreshers, especially when tools or laws change.
4. Communicate & Distribute
Make the policy accessible to all relevant users:
- Add it to your employee handbook
- Include it in onboarding materials
- Send out via internal communications with a summary of key points
5. Collect Employee Acknowledgements
Have all covered employees (and contractors, where applicable) sign an acknowledgment form confirming:
- They’ve read the policy
- They understand their responsibilities
- They agree to follow the rules
Store signed copies securely, and update them as the policy evolves.
6. Review & Update Annually
Technology and regulations move fast. Review the policy at least once a year, or sooner if:
- New AI tools are introduced
- Laws or industry standards change
- A major incident occurs
Keep a changelog of all edits, and notify employees of key updates.
Sample AI Policy
Below, you can see what an AI policy looks like. When you’re ready, you can customize this template and then download it in PDF or Word format.
