We are introducing AI-driven predictive maintenance in our service fleet, but our seasoned field technicians are ignoring the system's alerts and relying on their gut instinct. How do we address this lack of adoption without undermining their decades of valuable field experience?

Question

Tyler Smith · Accepted Answer

Seasoned technicians rely on their instincts because those instincts have kept them successful for decades. If you try to force them to blindly follow a computer program, they will resist, and you will lose their trust.

To bridge this gap, you must reframe the AI tool as an assistant that enhances their expertise, not a replacement for it. Use the GWC framework to evaluate the technicians' understanding of the new system. Do they truly get how the tool works, want to use it to make their jobs easier, and have the capacity to adopt it?

Next, build a collaborative verification process into your core workflows. When the predictive maintenance system flags an alert, make it a standard operating procedure for the technician to inspect the issue and log whether the AI was correct or incorrect.

This shifts their role from passive users to active experts who are training the system. Celebrate the moments where their gut instinct caught something the machine missed, and highlight the times the machine caught a hidden failure that saved them a return trip.

By involving your technicians in the loop, you respect their valuable experience while showing them the practical benefits of the technology.