This study aims to provide a comprehensive bibliometric analysis of the intersection between green supply chain management (GSCM) and artificial intelligence (AI). As environmental sustainability and digital transformation have become critical priorities for businesses, the integration of AI into GSCM practices has attracted increasing scholarly attention. In this context, the study analyzes the intellectual structure, development trends, and research patterns in this emerging field. Bibliometric data were collected from the Web of Science (WoS) database using relevant keywords, and the dataset was analyzed using the Biblioshiny application based on RStudio. The findings reveal a significant increase in the number of publications, particularly after 2017, indicating growing academic interest driven by sustainability concerns and technological advancements. The analysis also identifies the most influential authors, keywords, and thematic clusters, highlighting the evolution of research from conceptual discussions to more application-oriented studies focusing on performance, sustainability, and digital transformation. The results suggest that AI plays a transformative role in enhancing the efficiency, transparency, and environmental performance of supply chains. This study contributes to the literature by offering a structured overview of the research landscape and providing insights for future academic and practical developments in the field of AI-driven sustainable supply chain management.