Mapping AI-Driven Strategic Management and Technological Innovation Through Bibliometric Analysis

In response to the accelerating pace of digital transformation, this study conducts a bibliometric analysis to map global research trends at the nexus of artificial intelligence (AI), strategic management, and technological innovation. As AI increasingly reshapes competitive landscapes, organizations adopt data-driven strategies to enhance operational efficiency, foster innovation, and maintain strategic agility. The primary objective of this research is to systematically examine the intellectual structure and thematic evolution within this interdisciplinary domain. A comprehensive dataset of peer-reviewed publications indexed in the Dimensions database was analyzed using established bibliometric methods, including co-authorship, co-citation, bibliographic coupling, and keyword co-occurrence. Visualization and clustering were performed using VOSviewer to identify influential authors, institutions, countries, and research themes. The analysis reveals a significant convergence between AI applications and strategic management paradigms, with notable research foci emerging in areas such as innovation ecosystems, smart manufacturing, digital transformation, and dynamic capabilities. Leading contributions were predominantly from technologically advanced nations, indicating geographic disparities in research output and collaboration. The study also identifies critical gaps in the practical deployment of AI for strategic decision-making. These findings offer valuable insights for scholars, practitioners, and policymakers by providing a structured overview of the current knowledge base and suggesting directions for future inquiry. Ultimately, this work underscores the pivotal role of AI as a strategic enabler in fostering sustainable technological innovation across industries.