We want to establish a simple, pragmatic AI safety policy for our team that protects our client IP but doesn't slow down our operations. What are the non-negotiable guardrails we need to put in writing today?

Question

Tyler Smith · Accepted Answer

You do not need a fifty page legal document that your team will never read. A bloated policy will only encourage people to hide their AI usage, which creates massive security risks. You need a simple, one page set of guardrails that clarifies what is acceptable and what is off limits.

First, establish a strict data privacy rule. Your team must never input proprietary client data, personally identifiable information, or company financial data into public, consumer-facing AI models. If you use AI tools, ensure your team is using enterprise grade subscriptions where the vendor explicitly states that your data will not be used to train their public models.

Second, define the rule of human accountability. The person who inputs the prompt owns the output. If a team member delivers an AI-drafted document containing an error to a client, they cannot blame the machine. They must GWC™ the final deliverable.

Third, maintain a shared register of approved AI tools. If a team member wants to use a new software, they must bring it to their manager to ensure it meets your data security standards before logging in.

Review these simple rules during your departmental meetings to keep them top of mind. This keeps your business safe while encouraging your team to find creative ways to streamline their daily workflows.