Quality teams still inspect a sample of what comes off the line and investigate a defect's root cause well after it's already shipped. Yield prediction runs on last month's numbers, not this shift's, so a drifting process goes unnoticed until the returns start arriving.
AI inspects more of the line than a person can. Computer vision classifies defects from images as the product moves. Predictive models forecast yield and prioritize which lines need inspection first. Agents trace a defect back to its root cause on the process data, instead of a team doing it by hand. Fewer defects reach a customer, on infrastructure you control.