With the growing complexity of global supply chains, enterprises are confronted with severe challenges in resource coordination, demand forecasting, and dynamic process optimization. Traditional supply chain management (SCM) methods are often inflexible, reactive, and inefficient, which may lead to missed opportunities and revenue losses. Although technological progress has played a crucial role in addressing these challenges, and Generative Artificial Intelligence (GAI) has emerged as a transformative force with numerous advantages for SCM, existing literature on the role of GAI in enhancing supply chain performance still lacks a comprehensive theoretical framework for the construction of GAI applications and their empowerment mechanisms in SCM.
Therefore, Huamin WU from the School of Economics and Management, China University of Petroleum-Beijing, Guo LI from the School of Management, Beijing Institute of Technology, and Dmitry IVANOV from the Department of Business and Economics, Berlin School of Economics and Law have jointly conducted a research entitled “The Transformative Power of Generative AI for Supply Chain Management: Theoretical Framework and Agenda”.
This study first identifies the core GAI capabilities required for constructing the SCM framework, which are classified into five categories: learning and creativity, perception and prediction, expression and communication, collaboration and interaction, and adjustment and adaptation. It then explores the empowerment mechanisms of GAI in SCM, including driving improvements in demand forecasting, procurement management, inventory management, logistics management, and risk management. Meanwhile, the study analyzes the challenges faced by GAI in SCM application, such as data quality and availability issues, ethical and social implications, integration difficulties, high computational costs, and problems of accuracy and consistency, and proposes corresponding solutions. After that, the study points out the obvious gaps in existing research and puts forward a comprehensive research agenda, focusing on the SCM framework empowered by GAI, which is divided into technology-driven directions (including intelligent supply chain design and risk prediction, and the intersection of GAI with emerging technologies) and management innovation practices (including ethical and social implications of GAI, and sustainable supply chain design and low-carbon transition). The research results provide a theoretical basis and practical guidance for enterprises to effectively apply GAI in SCM and build flexible, robust, and sustainable supply chains.
The paper “The Transformative Power of Generative AI for Supply Chain Management: Theoretical Framework and Agenda” is authored by Huamin WU, Guo LI, and Dmitry IVANOV. Full text of the paper: https://doi.org/10.1007/s42524-025-4240-x.
