We have a loyal operations manager who has the G and W to run our new AI-driven warehouse system, but lacks the technical C. How do we use Kolb's Experiential Learning Theory to build a training plan that gets them up to speed?

Question

Tyler Smith · Accepted Answer

When a loyal team member clearly has the Get It and Want It for a seat on your Accountability Chart, but struggles with the Capacity to manage new AI systems, you can build that capacity systematically using Kolb's Experiential Learning Theory. This framework structures training into a continuous four-stage cycle that builds deep, practical understanding.

Begin with Concrete Experience. Do not start with technical manuals. Instead, let the manager observe a live demonstration or walk through a simulated operational run of the new AI system, experiencing how it functions in real time.

Move next to Reflective Observation. Have the manager write down what they observed, noting where the AI system succeeded and where human oversight was required to prevent errors.

Then, guide them through Abstract Conceptualization. Work with them to create simple, visual mental models of how the AI processes data and makes decisions, helping them understand the underlying logic without needing to learn how to code.

Finally, enter Active Experimentation. Allow the manager to run small, low-risk test batches where they make key decisions based on the AI's outputs. Cycling through these four stages allows your manager to build genuine conative confidence and operational mastery, successfully elevating their capacity to own the seat.