AI Is Rewriting Manufacturing Quality, Here’s What Changes

Описание: Manufacturing is in a new era where product cycles move faster, customer expectations are higher, and quality issues can scale globally before a team even realizes what is happening. This conversation is about what changes when AI becomes the system that connects the signals, accelerates investigation, and helps teams act with clarity.

Daniel First explains how manufacturers can move from reactive firefighting to proactive detection and resolution, even when the data is fragmented, unstructured, and spread across dozens of systems. The big idea is simple: the winners will not just ship faster, they will learn faster.

What you will learn in this episode
How manufacturers can detect customer impacting issues earlier, before downtime and warranty costs compound
Why solving issues can take hundreds of days, and how AI collapses the investigation timeline
How to separate real manufacturing AI from generic tooling, using three practical evaluation dimensions
What shifts inside quality, engineering, and cross functional teams as AI agents take on more of the investigative load
How “AI first” becomes measurable when strategy is operationalized and misalignment is exposed

Chapters
00:00 Manufacturing, speed, and the new quality reality
01:10 What Axion does and the problem it solves
05:10 Faster product cycles and the quality curve problem
10:05 Why issues can take hundreds of days to solve
16:20 How to evaluate AI solutions that actually work in manufacturing
22:40 Where quality roles are heading with AI agents
28:10 What “AI first” looks like when teams disagree on priorities

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