We want to allow our team to use generative AI for their daily tasks, but we are worried they will start using it as a crutch and lose their core problem-solving abilities. How do we write a policy that ensures our employees still retain complete ownership of their work under the GWC framework?

Question

Tyler Smith · Accepted Answer

Write your team AI policy around the core EOS principle of GWC: Get It, Want It, and Capacity to Do It. Every person on your Accountability Chart must retain absolute accountability for the output of their seat, regardless of the tools they use.

Your policy should state that AI is an assistant, not an employee. If a team member uses an AI model to draft a client report, write code, or create a production schedule, they are fully responsible for every word, line, and number. If the AI hallucinates a statistic or misses a critical operational detail, the human in that seat cannot use software error as an excuse.

To implement this, establish a policy with three strict rules. First, any AI-generated output must be reviewed and validated by a human before it is shared externally or integrated into company systems. Second, team members must understand the raw inputs they feed into the model, meaning they cannot use AI to bypass the basic training required to master their role. Third, if a team member cannot explain how a generated result was reached, they do not have the capacity to use that output.

By framing your AI policy around seat accountability rather than technical restrictions, you allow your team to innovate. They get to use AI to eliminate low-value tasks and speed up their workflows, but they remain 100 percent responsible for the final results. This keeps your operations sharp and ensures that as you scale, your people are still developing the real operational expertise your company needs to remain system-dependent.