Unveiling the AI–SCM Nexus: A Bibliometric and PRISMA-Based Review of Trends, Technologies, and Future Directions (2021–2025)

The integration of Artificial Intelligence (AI) into Supply Chain Management (SCM) has become a key driver of digital transformation, transforming industry practices and academic discourse. As global supply chains grow more complex and data-driven, AI’s role in improving efficiency, responsiveness, and sustainability has gained significant attention. This study conducts a bibliometric review of 499 peer-reviewed articles published between 2021 and 2025, sourced from Scopus and Web of Science, to trace the changing intellectual and thematic dimensions of AI–SCM research. Quantitative analysis using R Studio and network visualization via VOSviewer indicate key trends, prolific contributors, and dominant research clusters. The result indicates a significant rise in scholarly output over the past five years, with China, India, and the United States leading in publications. Institutions such as the Indian Institutes of Management and Penn State University emerge as major knowledge centers. The research identifies thematic focal points such as AI-assisted decision-making, supply chain resilience, risk management, and sustainability, closely associated to technologies such as machine learning, big data analytics, and Industry 4.0 frameworks. Network analysis reveals strong keyword co-occurrence around automation, optimization, digital supply chains, and predictive analytics, reflecting the convergence of AI capabilities with the fundamental SCM functions. Despite substantial progress, challenges remain—high implementation costs, shortages in skilled talent, data privacy issues, and ethical implications of AI application. These gaps underscore the need for more inclusive and responsible adoption strategies. This bibliometric paper provides a structured overview of the current research landscape, aiding scholars and practitioners in understanding key developments, influential authors, and emerging opportunities. The paper ends with a recommendation to organize future research on the topic of human-AI collaboration, governance systems, and socio-economic effects of AI on global supply-chains