AI Revolution in Chemistry is a practical, vendor-neutral field guide for chemists who want to use AI with confidence. It demystifies core methods—machine learning, deep learning, generative models, and digital twins—and shows how they create value from bench to plant: reaction prediction and synthesis planning, autonomous experimentation, materials design, process control (including PAT) and quality. Readers get durable principles and checklists for data, validation and scale-up; plain-English guidance on ethics, bias and regulation; and case-style examples that make clear where AI helps, where it fails and how to course-correct. Written for practising chemists (not data scientists), it keeps chemical intuition at the centre while providing just enough AI to be dangerous—in the best way. The result is a concise, actionable primer that stays relevant as tools evolve, helping teams design, pilot and scale projects across discovery, development and GMP.
