AI won't write your 8D for you — not one worth sending to a customer, anyway. That's where Rich Nave starts this conversation, and it sets the tone for everything that follows. The episode is a ground-level walkthrough of where AI actually earns its place in manufacturing problem-solving: not as a replacement for engineering judgment, but as something that helps teams move faster, stay focused, and stop reinventing the wheel.

The conversation covers four specific areas where manufacturers are already seeing real returns. First, problem definition — where AI can quickly generate multiple versions of a problem statement, giving teams a starting point instead of a blank whiteboard. Second, data analysis — where AI's ability to surface correlations across thousands of data points narrows an investigation from overwhelming to manageable (with a clear-eyed reminder that correlation is not causation, and that part is still human work). Third, organizational knowledge — how AI can index past 8Ds, articles, and solutions so teams stop resolving problems that were already solved, sometimes in a different plant, years ago.

The fourth area is where the numbers get hard to ignore: using AI to propagate the changes from a completed 8D into downstream documents — the PFMEA, control plan, LPA questions, standard work instructions. A process that typically takes a full day of skilled effort was completed in under thirty minutes in a recent real-world test. Not flawlessly — two of five AI-generated LPA questions had to be cut — but fast, and close enough that the human review step was the work, not the drafting.