A Review of Artificial Intelligence (AI) and Machine Learning (ML) for Supply Chain Resilience: Preliminary Findings

Global events (i.e., war in Ukraine, Covid-19) have highlighted the importance of developing resilient supply chains to deal with the increased frequency of interruptions. In response, organizations are increasingly seeking innovate ways to leverage AI and machine learning to enhance supply chain resilience (SCR). Anecdotal evidence suggests that AI and ML have potential to significantly enhance the resilience of supply chains. Despite its potential benefit, research on AI and ML is fragmented across academic disciplines due to the technical and managerial aspects of supply chains. This study aims to synthesize this fragmented body of knowledge to understand the link between AI, ML and how these technologies enhance the three dimensions of SCR, namely, readiness, responsiveness, and recovery. To achieve this aim, we conduct a systematic literature review of AI and ML research in the context of supply chain resilience that have been published between 2016 to 2022. The search strategy resulted in 153 studies, of which 24 primary studies form the basis of this study. The findings show that organizations that adopt AI and ML technologies enhance the resilience of their supply chains, as well as effective management of supply chains such as better decision-making, forecasting, supplier selection, and information processing. The study provides a roadmap for future researchers to advance understanding about the potential of these technologies.