Most of what is currently written about artificial intelligence in operations and supply chain management falls into one of three categories: academic treatments that arrive two years after the technology has moved on, consultant decks that promise transformation but never follow their authors home to a real plant, and vendor white papers that exist to sell a product.
What is missing is the practitioner’s voice — an operations leader who has actually opened a language model in the middle of a working day, with a real backlog of real problems, and made the technology earn its place.
This book is that voice.
The AI-Augmented COO is written for the Chief Operating Officer of a small or mid-sized manufacturer — between roughly one hundred and two thousand employees, the budget for an in-house AI team firmly at zero, the obligation to deliver this quarter undiminished. It is also written for the plant managers, supply-chain directors, quality leaders, and continuous-improvement professionals who will do most of the actual work of putting the technology into service.
The book makes one argument, then turns immediately to the question of how. The argument: generative AI changes the cognitive layer of operations — drafting, synthesis, analysis, the document work that surrounds every physical decision — by a factor that compounds quarterly for any leader who engages with it seriously. The factory floor is unchanged; the overhead surrounding it is not.
Inside you will find:
- A five-level maturity model
- A library of production-grade prompts
- Composite case studies
- Clear treatment of what AI must never be permitted to do in a factory
- A sober reading of the EU AI Act and CSRD implications for operations leaders
You will not find vision rhetoric, transformation roadmaps, or anything that requires a six-month project to begin returning value.
Examples throughout are drawn from a composite firm — MindEx.Pro, a fictional Eastern European machine-builder. The firm is invented. The operational patterns are not.