Towards Explainable Artificial Intelligence (XAI) in Supply Chain Management: A Typology and Research Agenda

Abstract

The potential for artificial intelligence (AI) to drive digital supply chain transformation today is beyond question. However, its full potential to address more complex supply chain management (SCM) problems is still unclear partly due to AI’s black-box problem both in practice and in literature. This paper attempts to highlight the significance of explainable AI (XAI) in SCM and shades light on SCM areas where AI’s black-box problem remains problematic. The goal of this integrative literature review paper is to provide new insight into the status of XAI as a solution to AI’s black-box problem in SCM where AI techniques have made rapid in-roads. The AI techniques in SCM literature and the significance of XAI in SCM are contrasted. We present an integrative research typology for XAI in SCM to better align how SCM literature has conceived AI deployment in SCM this far. The typology should help us understand the gap between what we know about AI deployment in practice, AI maturity in SCM, and the extent of XAI in SCM .