An analytical review of artificial intelligence applications in sustainable supply chains

Sustainable supply chains are essential for promoting environmental responsibility, economic efficiency, and social well-being. They help reduce carbon footprints, optimize resource use, and support circular economy initiatives. Economically, they enhance efficiency, lower costs, and mitigate risks related to resource scarcity and environmental regulations. Socially, they ensure ethical sourcing, fair labor practices, and corporate social responsibility. By balancing these dimensions, sustainable supply chains contribute to business resilience while aligning with global sustainability goals, such as the UN Sustainable Development Goals (SDGs). In the age of Artificial Intelligence (AI), rapid technological advancements have significantly transformed supply chain operations, necessitating greater flexibility and the integration of AI-driven techniques. The application of AI in supply chain management has proven highly beneficial, offering enhanced efficiency, predictive capabilities, and improved sustainability. Recent advancements, including Large Language Models (LLMs), are also playing a transformative role in enhancing decision-making and risk management across supply chains. Numerous researchers have highlighted AI's potential in advancing circular economy initiatives by optimizing resource utilization and minimizing waste. However, despite the growing academic interest, research in this domain remains fragmented and lacks a coherent structure. To address this gap, this paper conducts a comprehensive bibliometric analysis to map the current research landscape, identify key themes, and highlight future directions. Bibliographic records were retrieved from the Web of Science database, covering the period from 1997 to 2024. A total of 1,070 records were initially gathered for analysis. The findings of this study provide valuable insights into the evolution of research in AI-driven sustainable supply chains, uncover emerging trends, and suggest potential avenues for future exploration. Specifically, the analysis reveals an annual publication growth rate of 23.37% from 1997 to 2024, with China, India, and the USA as the top contributing countries. Core research themes include AI-enabled logistics optimization, circular economy practices, and supply chain resilience under global disruptions. By offering a structured overview of the field, this study aims to support scholars and practitioners in navigating the intersection of AI and sustainability in supply chain management. • Review 25 years of technology in sustainable supply chains • Map global studies on artificial intelligence in supply chain practices • Show the rapid growth in tech-driven supply chain resilience research • Identify top countries, authors, and journals in the research landscape • Explore future paths for more intelligent and greener supply chain systems