The transformative power of generative AI for supply chain management: Theoretical framework and agenda

Abstract

The increasing complexity of global supply chains has presented critical challenges for businesses in coordinating resources, forecasting demand, and dynamically optimizing processes. Traditional supply chain management (SCM) methods are often inflexible, reactive, and prone to inefficiencies, which can result in missed opportunities and lost revenue. Technological advancements have played a pivotal role in addressing these challenges, with Generative Artificial Intelligence (GAI) emerging as a transformative force that offers numerous advantages for SCM. Despite the abundance of literature on the role of GAI in enhancing supply chain performance, it remains insufficient in providing a comprehensive theoretical framework for the construction of GAI applications and their empowerment mechanisms within SCM. This study first outlines the core GAI capabilities necessary for constructing the SCM framework. We then examine the empowerment mechanisms and challenges of GAI in SCM and propose corresponding solutions. Afterward, we discuss notable gaps and propose a comprehensive research agenda, focusing on the SCM framework empowered by GAI.

Graphical abstract

Keywords

generative artificial intelligence / supply chain management / theoretical framework

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Competing Interests

The authors declare that they have no competing interests.

RIGHTS & PERMISSIONS

2025 Higher Education Press