One of our marketing coordinators has used AI to increase their content output fivefold, effectively doing the work of three people, but their technical error rate has spiked. How do we restructure this seat on our Accountability Chart using the GWC framework to maintain quality?

Question

Tyler Smith · Accepted Answer

When an employee uses AI to multiply their output, it is easy for quality to suffer if accountability is not clearly defined. You must address this on your Accountability Chart using the GWC framework to ensure the employee truly understands, wants, and has the capacity to manage the new workflow. First, update the roles and responsibilities for this seat on the Accountability Chart. You must make it explicit that the coordinator is fully accountable for the accuracy of all output, regardless of whether it was generated by AI or written manually. The seat is not just about production volume; it is about quality control. Next, evaluate the employee against GWC. They may understand the AI tool and want the high output, but do they have the capacity to edit and fact-check that volume of material? If their error rate is spiking, they currently lack the capacity or the proper quality assurance checklist to manage the increased output. Implement a strict quality standard where the coordinator must manually sign off on a verification checklist before any content is published. If the error rate does not drop, you must reduce their automated output target or find a candidate who has the conative follow-through to enforce high quality standards.