The relationship between artificial intelligence and leadership has become a central area of debate, transforming contemporary management approaches by restructuring organizational decision-making processes, managerial roles, and human–machine interaction. The increasingly widespread adoption of artificial intelligence in organizations has led to a growing body of conceptual and empirical research addressing the function of leadership, required competencies, and ethical responsibilities. This rapid and fragmented body of work has created a need for a holistic assessment of the field’s developmental trends, dominant thematic foci, and intellectual structure. Accordingly, this study aims to comprehensively examine the developmental trajectory, thematic orientations, and knowledge production patterns of academic publications that jointly address the concepts of artificial intelligence and leadership through a bibliometric method. In this context, 2,064 articles retrieved from the Web of Science database were analyzed using the RStudio-based Biblioshiny software. The analysis covered scientific production over time, influential journals, authors, and countries, citation structures, keyword patterns, thematic maps, and conceptual networks. The findings reveal that the artificial intelligence and leadership literature has gained significant momentum in recent years and exhibits a distinctly interdisciplinary structure. While core concepts such as artificial intelligence, leadership, decision-making, and learning occupy a central position in the literature, themes including ethics, sustainability, transformational leadership, digital transformation, and employee-centered perspectives are addressed with varying levels of emphasis. Thematic mapping and network analyses indicate that the field represents a multilayered research domain in which technological, managerial, and human dimensions are discussed simultaneously rather than a homogeneous structure.