Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions
Giovanna Culot, Matteo Podrecca, Guido Nassimbeni
Abstract
This article presents a systematic literature review (SLR) of empirical studies concerning Artificial Intelligence (AI) in the field of Supply Chain Management (SCM). Over the past decade, technologies belonging to AI have developed rapidly, reaching a sufficient level of maturity to catalyze transformative changes in business and society. Within the SCM community, there are high expectations about disruptive impacts on current practices. However, this is not the first instance where AI has sparked business excitement, often falling short of the hype. It is thus important to examine both opportunities and challenges emerging from its actual implementation. Our analysis clarifies the current technological approaches and application areas, while expounding research themes around four key categories: data and system requirements, technology deployment processes, (inter)organizational integration, and performance implications. We also present the contextual factors identified in the literature. This review lays a solid foundation for future research on AI in SCM. By exclusively considering empirical contributions, our analysis minimizes the current buzz and underscores relevant opportunities for future studies intersecting AI, organizations, and supply chains (SCs). Our effort is also meant to consolidate existing research insights for a managerial audience.