Intelligent Supply Chain Management: A Systematic Literature Review on Artificial Intelligence Contributions

This systematic literature review investigates the recent applications of artificial intelligence (AI) in supply chain management (SCM), particularly in the domains of resilience, process optimization, sustainability, and implementation challenges. The study is motivated by gaps identified in previous reviews, which often exclude literature published after 2020 and lack an integrated analysis of AI’s contributions across multiple supply chain phases. The review aims to provide an updated synthesis of AI technologies—such as machine learning, deep learning, and generative AI—and their practical implementation between 2021 and 2024. Following the PRISMA framework, a rigorous methodology was applied using the Scopus database, complemented by bibliometric and content analyses. A total of 66 studies were selected based on predefined inclusion criteria and evaluated for methodological quality and thematic relevance. The findings reveal a diverse classification of AI applications across strategic and operational SCM phases and highlight emerging techniques like explainable AI, neurosymbolic systems, and federated learning. The review also identifies persistent barriers such as data governance, ethical concerns, and scalability. Future research should focus on hybrid AI–human collaboration, transparency through explainable models, and integration with technologies such as IoT and blockchain. This review contributes to the literature by offering a structured synthesis of AI’s transformative impact on SCM and by outlining key research directions to guide future investigations and managerial practice.