Part 2: Execution Intelligence: Embedding AI Inside Validated Manufacturing

By Nikki Bishop, Emerson

Analytics that sit apart from validated execution lose the context quality and release decisions depend on. Enterprise data platforms stay. What changes is where AI does its work: inside governed workflows, with batch context and QA authority behind every output. The architecture described here separates a system that merely flags a yield trend from one that detects drift in a specific unit procedure, ties it to supplier lot genealogy, and routes a deviation through controlled review with full traceability. It also shows how this shifts the criteria for judging digital initiatives, particularly as batch sizes shrink and real-time release strategies mature. Read the article to see how that works in practice.