AI Acceptable Use Policy
What This Requires
Establish and publish a formal AI Acceptable Use Policy defining permitted AI use cases, prohibited activities, data handling requirements, and approval workflows. Policy must be approved by executive leadership and updated annually.
Why It Matters
Without clear boundaries, employees may use AI tools inappropriately, exposing sensitive data or generating biased outputs. A formal policy establishes accountability and sets organizational risk appetite for AI adoption.
How To Implement
Draft Core Policy Document
Define permitted use cases (code generation, content drafting, data analysis) and prohibited activities (automated decision-making affecting individuals, processing regulated data without review, bypassing security controls). Include approval workflow for new AI tools.
Establish Governance Structure
Designate policy owner (CISO or CTO), define review cycle (annual or triggered by incidents), and create exception process for high-value use cases requiring deviation.
Communication & Training
Publish policy to internal wiki/intranet, require annual acknowledgment, and deliver role-specific training (engineers get code review standards, analysts get data handling rules).
Enforcement Mechanisms
Integrate policy into HR onboarding, technical controls (blocklists, DLP rules), and incident response. Document consequences for violations (warning → suspension → termination).
Evidence & Audit
- Signed policy document with executive approval
- Policy publication record (wiki/intranet timestamp)
- Training completion reports and acknowledgment logs
- Exception request records with approval chain
- Incident reports showing policy enforcement