AI Policy Framework

Establish clear boundaries and guidelines for AI usage within your organization with this comprehensive policy framework.

Core Principles

Every AI policy should be built on these foundational principles:

1. Transparency - Be clear about when and how AI is used
2. Accountability - Humans remain responsible for AI-assisted outputs
3. Security - Protect sensitive data from exposure
4. Quality - Maintain standards through human review

Key Policy Areas

Data Protection

Rule: No proprietary code in public LLMs

Never input the following into public AI tools:

• Source code
• API keys or credentials
• Customer data
• Financial information
• Strategic plans
• Legal documents

Human Oversight

Rule: Human review required for all AI output

Every AI-generated output must be:

• Reviewed by a qualified human
• Validated for accuracy
• Checked for bias or errors
• Approved before publication/use

Policy Template

Copy this template to create your organization's AI usage policy:

Implementation Checklist

When rolling out your AI policy:

• Executive sponsorship secured
• Legal review completed
• IT security assessment done
• Training materials developed
• Communication plan created
• Monitoring tools in place
• Incident response defined
• Review schedule established

Quick Reference: Do's and Don'ts

Do

• Use AI as an assistant, not a replacement
• Verify all AI outputs before use
• Report suspicious AI behavior
• Stay updated on policy changes
• Use approved tools only

Don't

• Share confidential data with AI
• Publish AI output without review
• Bypass security controls
• Assume AI is always correct
• Use personal AI accounts for work