Abstract: Artificial Intelligence(AI) technology has experienced rapid development in recent decades, driving a profound paradigm shift in management science research and reshaping the theoretical framework, research methodologies, and practical application scenarios of the discipline. To systematically sort out the path, current situation, and challenges of the integration of AI and management science, this study conducted a large-scale quantitative analysis of high-quality journal literature indexed in the Web of Science database, with a focus on publications included in the Financial Management Society (FMS) journal list, and constructed and clarified the systematic framework of its fundamental transformation. This method covers 25,719 literatures in the fields of management science and economic science from 1996 to 2025, and uses professional analytical tools such as VOSviewer and RStudio to conduct visual analysis of keyword co-occurrence relationships, national cooperation networks, and research trend evolution. The results show that the number of publications in this field presents an exponential growth trend over the past three decades, with China and the United States as the core contributing countries; there are significant differences in the research focus between management science and economic science; research hotspots are concentrated in key clusters such as the application of AI technology in management practice, the identification and response to algorithmic risks, the construction of trust mechanisms in service science under the intelligent environment, and the AI-driven digital transformation of enterprises, while notably, significant differences exist in the research focus of management science and economic science during the integration process—management science tends to prioritize the optimization of practical management scenarios and efficiency improvement, while economic science focuses more on exploring the impact of AI on economic operation rules and resource allocation mechanisms. The conclusion indicates that AI has evolved from an auxiliary tool to a core driving force for promoting the reconstruction of management science theories and the transition of research paradigms towards the "human-object-information" three-dimensional space. Future research should focus on cutting-edge issues such as the internal mechanism of human-machine collaboration, the ethical boundaries of algorithm governance, and institutional adaptation in major decision-making, so as to promote the construction of a new management science theoretical system adapting to the intelligent era.