When employees use AI to execute work they do not fully understand, how do we objectively measure the Capacity component of GWC on our Accountability Chart?

Question

Tyler Smith · Accepted Answer

A dangerous operational failure occurs when an employee relies on AI to produce deliverables that exceed their personal comprehension. If a junior staff member uses a prompt to generate an advanced financial model or legal memorandum, but cannot explain the math or identify a hallucinated citation, they do not have the Capacity to do that job.

GWC stands for Get it, Want it, and have the Capacity to do it. Capacity is not simply having the technical skill to click buttons or type prompts. Capacity means possessing the intellectual rigor, emotional capacity, and domain knowledge required to evaluate the quality of the final output. If an individual cannot spot a critical error in an AI-generated deliverable, they fail the Capacity test.

To evaluate Capacity objectively, test your team members on the mechanics behind the output. Ask them to explain the rationale of a recommendation without referencing the software prompt. If they cannot defend the conclusions, you must either coach them on the underlying fundamentals or move them to a seat that aligns with their actual capability.

Never allow team members to hide behind machine intelligence. When your leadership team runs quarterly People Analyzer reviews, insist that Capacity includes deep domain comprehension. A company full of operators who generate work they cannot critique is an accident waiting to happen, exposing you to severe client churn and valuation discounts.