AI in Supply Chains

Bringing together some of the world’s foremost supply-chain thinkers, this book shows how artificial intelligence (AI) is rewriting the rules of global supply chain management. It explores machine learning, computer vision, large-language models, and generative AI in action – how they’re used to refine demand forecasts, optimize inventories, and drive down costs while service levels soar. The book examines AI-driven demand forecasting and inventory optimization, which enhances the accuracy of predicting customer demand and managing inventory levels to reduce costs and improve service. It covers intelligent logistics and transportation management, and utilizing AI to optimize routing, scheduling, and fleet management, which leads to increased efficiency and sustainability. The discussion extends to procurement and supplier relationship management, where procurement processes are streamlined and supplier partnerships are strengthened through AI-driven analytics and decision-making tools. In turn, the book confronts the hard questions of ethics, data privacy, and algorithmic bias, equipping readers to harness AI’s power responsibly and ethically across the entire supply chain.
These topics are vital, as they address the pressing need for supply chains to become more agile, resilient, and responsive in today’s rapidly changing global market. By exploring these areas, the book aims to provide readers with a nuanced understanding of the current landscape and future directions of AI in supply chain management. The problem this book sets out to solve is the knowledge gap between the theoretical potential of AI and its practical application within supply chains around the globe. By presenting real-world examples, case studies, and expert analyses, it offers actionable insights that can be applied to enhance operational efficiency and strategic decision-making.
The book is intended for supply chain professionals, business leaders, academics, policymakers, and students seeking a better grasp of the intersection of AI and supply chain management. It serves as both a reference guide and a source of inspiration for those looking to leverage AI technologies to drive innovation and competitiveness in their organizations.

Tinglong Dai is the Bernard T. Ferrari Professor of Business at Johns Hopkins University, specializing in human-AI interaction, healthcare analytics, and global supply chains. He developed and teaches the core MBA course “Data Science: Artificial Intelligence” and was named one of Poets & Quants’ Top 40-Under-40 Business School Professors. His work is widely featured in major media outlets and he has spoken at prestigious events including commencements at Carnegie Mellon and Johns Hopkins. Dr. Dai serves as Vice President of Marketing, Communication, and Outreach for INFORMS and holds editorial roles at leading journals. His award-winning research spans top publications in operations and management science.
Maxime C. Cohen is a Professor at McGill University, Canada and Scale AI Chair in Data Science for Retail. He directs research at the Bensadoun School of Retail Management and advises companies on AI, pricing, and retail strategy. A former Visiting Professor at Yale and Research Scientist at Google AI, Dr. Cohen has collaborated with major firms including Meta, Uber, and L’Oréal. His research spans operations, data science, and sustainability, earning over 40 awards including Poets & Quants’ Top 40-Under-40 and the MSOM Young Scholar Prize. He also serves as Chief AI Officer at ELNA Medical and Scientific Director of MyOpenCourt.org.