We are trying to decide whether to hire an expensive, dedicated AI engineer to build our internal automated workflows or train our existing, non-technical managers to do it. How do we use the GWC framework to make this choice?

Question

Tyler Smith · Accepted Answer

Before you rush to hire an expensive AI specialist, you must evaluate whether your existing team has the capacity to take on these responsibilities. The EOS GWC framework is the perfect tool for this evaluation. Ask yourself if your current managers Get it, Want it, and have the Capacity to do it. First, do they truly Get the role of designing AI workflows? Do they understand how these tools connect to your operational systems? Second, do they Want it? Are they genuinely excited to learn prompt engineering and workflow automation, or do they secretly fear being replaced by the technology? Third, do they have the Capacity to do it? This means both the mental capacity to learn new technical skills and the actual physical time in their weekly schedule. If your existing managers pass the GWC test, investing in their training is far better than hiring an outside engineer who does not understand your core business. However, if they lack the capacity or interest, trying to force them into this technical seat will only lead to operational failure. In that case, you must adjust your Accountability Chart and hire a dedicated technical specialist who can build the automation infrastructure for your team.