That's a really insightful question that gets to the heart of what's happening in industrial maintenance right now. You're right to be concerned about the balance between new technology and traditional skills.

From what I'm seeing, AI-powered predictive maintenance isn't eliminating maintenance technicians - it's transforming their role. Instead of being reactive troubleshooters who rush to fix broken equipment, technicians are becoming proactive system managers. The AI gives them a 72-hour heads-up, but someone still needs to interpret those predictions, plan the maintenance work, coordinate parts and labor, and actually perform the repair.

The real shift is from "break-fix" to "predict-prevent-optimize." Technicians now need to understand data analytics, interpret AI alerts, and make strategic decisions about when and how to intervene. They're becoming more like system health managers than emergency responders.

As for your concern about creating "button-pushers" - that's a real risk if training doesn't evolve. The best approach seems to be hybrid training: maintaining core electrical and mechanical troubleshooting skills (including relay ladder logic) while adding data science literacy. Technicians need to understand both the physical systems AND the digital systems monitoring them.

The AI handles pattern recognition across massive datasets, but human judgment is still crucial for context, exceptions, and complex system interactions. The technician who can bridge both worlds - understanding traditional controls AND modern analytics - will be incredibly valuable.

What do you think - are you seeing this shift in your workplace?