Episode 1: AI in Quality Management #QualityMatters2.0
AI can save you time, but what happens when you can’t explain how it reached an answer? That’s a problem in any quality system. It’s also where we think the AI hype needs a little reality check. In Episode 1, Kyle Chambers and Caleb Adcock return after a long break, share an update on the TQA app, and get into where AI may actually help quality teams.
The biggest theme is simple: use AI as a tool, not an authority. If a report, calculation, or recommendation matters, you still need to verify the source. You should also understand how the system produced the result. The same applies to audits and inspections. An experienced auditor notices context, inconsistencies, and shop-floor details that a yes-or-no system can miss.
There’s also a people side to this. Automating every easy task may save time today. But it can remove work that helps newer employees build judgment and experience. We also discuss customer-data separation, software permissions, and why AI should start with narrow, useful jobs before it reaches critical decisions. AI is moving fast, but quality still depends on traceability, experience, and someone willing to check the work.
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