In recent years, artificial intelligence (AI) has significantly impacted various sectors, including education, where it has transformed pedagogical practices, teacher training, and curriculum development. The integration of AI in these areas offers promising opportunities to enhance instructional quality and address diverse learner needs through personalized educational experiences. However, a key component of successful AI integration, “educational leadership”, remains notably underrepresented in current research. The purpose of this bibliometric study is to examine the representation of leadership within the corpus of research at the intersection of AI, teacher training, and pedagogy from 2014 to 2024, utilizing data derived from Scopus and visualized through VOSviewer. By focusing on this underexplored aspect, this study seeks to understand and quantify the extent to which leadership is addressed, or omitted, in existing research, and to elucidate its implications for global educational practices and policies. This study employs a rigorous bibliometric methodology, integrating science mapping and co-occurrence analysis to examine the thematic structure and research trends surrounding AI, teacher training, pedagogy, and leadership. The bibliographic data was sourced from Scopus, selected for its extensive coverage and reliable indexing of peer-reviewed research publications, spanning from 2014 to 2024. To focus the dataset on studies explicitly relevant to our research question, a systematic search string was crafted, incorporating keywords across four thematic areas: artificial intelligence, teacher training, pedagogy and leadership. A lack of leadership discourse may indicate an oversight that has implications for the sustainability and effectiveness of AI-driven initiatives in education. Without strong leadership to advocate for, implement, and manage these technologies, the potential benefits of AI for enhancing teacher training, curriculum development, and pedagogy may not be fully realized or may face significant challenges in practical application. Leadership is crucial in navigating the complexities associated with technological change, addressing concerns such as ethical use, data privacy, teacher preparedness, and alignment with educational goals. The underrepresentation of leadership perspectives in the current literature suggests that there may be insufficient guidance or frameworks for educational leaders to draw upon as they undertake AI integration in their institutions. This oversight could contribute to several challenges, such as teacher resistance to new technologies, inadequate professional development support, and inconsistency in AI application across institutions. Furthermore, the absence of leadership emphasis may hinder policy development at both institutional and governmental levels, where well-defined leadership strategies are essential for orchestrating large-scale educational reforms. The study highlights an urgent need to incorporate leadership perspectives into research on AI in education, emphasizing that leadership is not merely a supporting element but a foundational one in ensuring successful and sustainable AI integration.

Keywords: Artificial intelligence (AI) in education, Teacher training, Educational leadership, AI-driven teacher training, Leadership in educational technology, Curriculum development, Professional development, Instructional leadership.