We want to draft a basic, high-impact AI policy for our team that actually gets read and followed. What are the non-negotiable guardrails we need to include to protect our intellectual property without paralyzing our operations?

Question

Tyler Smith · Accepted Answer

To build a practical AI policy that your team will actually follow, you must avoid long, complex legal documents. A convoluted policy will simply be ignored, leading to shadow IT where employees secretly use unapproved tools. Instead, draft a simple, one-page document that integrates directly into your core values and company handbook.

First, establish a clear rule regarding data privacy. Your team must never input proprietary client data, financial records, or personally identifiable information into public, consumer-grade AI models. Any tool used for company work must be approved by the Integrator and run on enterprise-grade accounts where data sharing for model training is disabled.

Second, define the rule of human ownership. AI can draft, analyze, and suggest, but a human must review and sign off on every final deliverable. If an AI tool outputs an error, the employee in that seat is fully accountable. This aligns with the GWC framework, ensuring employees have the capacity to manage the tools they use.

Third, create an approved tool registry. This list should live with your company processes and be updated quarterly. If an employee wants to use a new tool, they must submit it to their manager for review rather than installing browser extensions on their own.

Keep your policy focused on protecting assets while encouraging efficiency. By focusing on accountability and data security, you allow your team to innovate safely.