Artificial Intelligence in Supply Chain Management: A Bibliometric and Science Mapping Analysis of Research Evolution and Service-oriented Transformation (2000–2025)
Abstract
Artificial intelligence (AI) applications in supply chain management (SCM) have surged since 2016, with a pronounced acceleration after 2021, driven by advances in machine learning, robust data infrastructures, and the digitization of supply chain processes. This study analyzes the evolution of the field through bibliometric performance assessment and science mapping, drawing on a Scopus dataset filtered to 2,515 English-language journal articles published between 2000 and 2025. The trajectory of the field began with early AI-driven decision support and forecasting based on neural networks and genetic algorithms, shifted mid-period toward predictive analytics and traceability, and now emphasizes machine learning, deep learning, blockchain, the Internet of Things, Industry 4.0, and digital twin technologies for resilience and sustainability analytics. The thematic structure reveals a transition from optimizing internal product flows toward developing scalable, AI-enabled service capabilities, such as visibility, risk analytics, and decision intelligence that are embedded within service supply chain ecosystems. The analysis combines performance metrics, including annual production, citations, the h-index, and author, affiliation, country, and journal productivity, with science mapping, including co-word analysis, co-authorship, bibliographic coupling, and co-citation, following established bibliometric workflows and normalization protocols. All figures were generated directly from the dataset using reproducible Python pipelines and VOSviewer-style network visualization, so that every reported value is consistent with the underlying corpus of 2,515 articles. Overall, the study concludes that AI in SCM is shifting from internal optimization toward AI-enabled service capabilities, and it outlines a research agenda for governing and sustaining these service-oriented configurations within digital supply chain ecosystems.