Overview

Inventory management sits at the crossroads of strategy, operations, and technology, where even small decisions can ripple across the entire supply chain. As markets become more volatile, customer expectations rise, and product lifecycles shorten, traditional planning methods struggle to keep pace. Artificial Intelligence (AI) has emerged as a powerful catalyst for change-transforming how organizations forecast demand, optimize stock levels, manage costs, and orchestrate warehouse operations. More recently, Generative AI has added a new dimension by enabling systems that not only analyze historical data but also generate scenarios, recommendations, and decision insights that mirror human reasoning at scale. This book, AI and Generative AI for Inventory Management, is designed as a practical and forward-looking guide for students, professionals, and decision-makers seeking to harness these technologies effectively. Through a structured progression-from foundational concepts and core technologies to advanced applications, real-world projects, and future trends-the chapters explore how AI-driven intelligence can be embedded across the inventory lifecycle. By blending theory, use cases, and hands-on projects, the book aims to bridge the gap between conceptual understanding and real-world implementation, equipping readers to design smarter, more resilient, and adaptive inventory systems in an AI-powered supply chain ecosystem

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