Authors - Lankalapalli Vamsi Krishna, Santanu Mandal Abstract - The rapid advancement of generative and agentic artificial intelligence (AI) is significantly transforming research in operations management and supply chain systems. Despite the substantial increase in scholarly output in recent years, the structural evolution and thematic consolidation of this interdisciplinary field remain insufficiently mapped. This study presents a bibliometric analysis of 116 Scopus-indexed articles published between 2015 and 2025 to examine publication trends, knowledge concentration, intellectual structure, and longitudinal thematic transitions. Utilizing the Bibliometrix R package, the analysis employs performance metrics, Bradford’s Law, keyword co-occurrence mapping, thematic centrality–density analysis, and temporal evolution modeling. The results indicate accelerating research growth and increasing consolidation within core engineering-oriented journals. Intellectual clustering reveals strong integration between computational modeling, reinforcement learning, and supply chain decision systems. Thematic mapping identifies computational methods and autonomous agents as central themes, while generative AI emerges as a developing yet increasingly interconnected trajectory. Longitudinal analysis reveals a clear shift from agent-based simulation frameworks toward adaptive, autonomous, and AI-integrated operational ecosystems. The findings suggest that generative and agentic AI are becoming foundational elements of next-generation operational intelligence systems. This study provides structured insights into the maturation of AI-enabled operational research and offers guidance for future interdisciplinary investigations in autonomous supply chain intelligence.
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