This is such a relatable challenge! I feel your pain - it's like wanting to build a smart home when you're still figuring out how to change a lightbulb. The excitement of AI vision systems for quality control is real (who wouldn't want that precision?), but if your maintenance team is struggling with ladder logic basics, you're setting everyone up for frustration.

Here's what I'd suggest: First, don't think of this as an either/or situation. AI should amplify human expertise, not replace it. Start by identifying specific problems where AI vision could make the biggest impact - maybe it's detecting subtle defects that humans miss consistently. Then, create a parallel training program for your maintenance team.

The key is incremental implementation. Consider piloting AI vision on one production line while simultaneously investing in ladder logic training. Use the AI system to generate insights that actually help your maintenance team - like predicting when equipment might fail based on visual patterns. This way, they see AI as a tool that makes their jobs easier, not a threat.

Also, look for AI solutions with user-friendly interfaces that don't require deep technical knowledge to operate. Many modern systems are designed to be maintained by technicians with traditional skills, while the complex AI algorithms run in the background.

Remember, the goal isn't to have a maintenance team that can code neural networks - it's to have a team that can effectively use AI tools while maintaining their core competency in industrial automation. It's about creating a culture of continuous learning where both the technology and the team evolve together.