We are building our hiring plans for the next twelve months but do not know how to assess the GWC™ of new hires when their primary job will be managing AI tools rather than executing manual tasks. How do we screen and plan for these hybrid seats on our Accountability Chart?

Question

Tyler Smith · Accepted Answer

When AI handles the execution of routine tasks, your hiring plans must shift from finding specialized technical executors to finding strategic problem solvers. When evaluating candidates for seats on your Accountability Chart, you must redefine how you measure GWC™ (Get It, Want It, Capacity to Do It). The capacity component is no longer about manual output speed; it is about the ability to direct and audit AI-generated work.

Begin by identifying the cumbersome processes that currently keep your employees trapped in low-value tasks. As you plan your future hiring, design your job descriptions around the assumption that the new hire will use AI tools to execute eighty percent of the baseline production. Your goal is to hire individuals who can analyze, refine, and contextualize that AI-generated output for your clients.

Gradually evolve your existing seats to match this hybrid model. Update your hiring scorecard to test candidates on their ability to prompt, evaluate, and synthesize data rather than perform repetitive data entry or baseline drafting. This ensures you build a lean, high-performing team that can scale your operational capacity exponentially without ballooning your payroll or introducing redundant human execution.