Artificial Intelligence (AI) is rapidly reshaping educational systems, influencing pedagogical practices, learning environments, and institutional decision-making. While scholarly interest in AI in education has grown exponentially, the field remains fragmented across disciplines, regions, and thematic orientations. To address this gap, the present study conducts a comprehensive bibliometric analysis of 5676 peer-reviewed articles indexed in Scopus. The study looks at global research trends, collaboration patterns, and new topic groups by analyzing how often articles are cited together, mapping keywords that appear together, and visualizing networks of authors who work together. Findings reveal a marked surge in research activity over the past five years, with heightened interdisciplinary collaboration and the rise of themes such as personalized learning, intelligent tutoring systems, ethical considerations, and generative AI. Despite this growth, significant gaps persist in the areas of equity, policy integration, and the inclusion of underrepresented regions and perspectives. This study adds to academic discussions by providing a comprehensive and worldwide perspective on how AI is being used in education, while also pointing out important areas for future research, ethical guidelines, and inclusive educational improvements.