When one team member delivers double the output of their peers using self-taught AI techniques, how do we address this on the Accountability Chart without penalizing the other employees?

Question

Tyler Smith · Accepted Answer

When an individual contributor dramatically outperforms their peers by leveraging AI, leadership often mistakenly assumes the top performer has superior capacity while the rest have a performance issue. In reality, you are looking at an operational systems gap, not a GWC failure.

Begin by identifying the variance. In your next Level 10 Meeting, bring the productivity disparity to the Issues List. Do not penalize the standard performers who are following the documented Core Process. At the same time, do not keep the top performer's AI workflows isolated in a silo.

Your immediate strategic priority is to institutionalize the top performer's method. Create a 90-day Rock to extract the specific prompts, tool combinations, and operational sequences that employee is using. Turn those individual habits into an updated, documented Core Process that belongs to the entire company.

Once the process is documented, update the training expectations across that seat on the Accountability Chart. Provide the rest of the team with structured coaching on how to run the new AI-augmented workflow. Give them a realistic 30-to-60-day window to adopt the tools.

If an employee still cannot hit the elevated output standard after receiving clear training and access to the automated systems, then you have a genuine GWC issue regarding Capacity. At that point, you address it directly through the People Analyzer. Elevate the system first; evaluate individual capacity second.