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.