Leadership in Human-AI Teaming: A Bibliometric Analysis of Collaboration, Trust, and Performance
Year: 2026
Type: article
Abstract: The rapid integration of artificial intelligence (AI) into organizational work has transformed conventional approaches to teamwork, leadership, and decision-making, creating a growing research domain centered on human–AI teaming. This study aims to examine the intellectual structure, research development, and emerging themes in the literature on leadership in human–AI teaming, with particular attention to collaboration, trust, and performance. A bibliometric analysis was conducted using 43 documents indexed in the Scopus database, with VOSviewer employed to visualize co-authorship and keyword co-occurrence networks. The analysis examined publication trends, subject areas, institutional and country contributions, collaboration patterns, and the conceptual relationships among major research themes. The findings indicate a substantial recent expansion of research in this field, with Computer Science representing the largest subject area, followed by Business, Management and Accounting, Economics, Engineering, and Social Sciences. The co-authorship analysis demonstrates increasing collaboration across countries, institutions, and multidisciplinary research groups. The keyword analysis identifies artificial intelligence, decision making, human resource management, leadership, autonomous agents, intelligent agents, and human-agent teaming as central themes. The temporal analysis further indicates a shift from technology-oriented research toward more sophisticated forms of human–AI collaboration and organizational integration. The findings suggest that leadership, collaboration, trust, and performance should be examined as interconnected dimensions rather than isolated research topics. This study contributes to the literature by mapping the development of leadership research within human–AI teaming and identifying opportunities for future research on leadership mechanisms, calibrated trust, collaborative processes, and team performance in AI-enabled work environments.
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225310330