Artificial Intelligence in Education: A Knowledge Mapping Approach and Discussion of Humanisation Challenges

Abstract The integration of artificial intelligence (AI) in education is transforming traditional teaching paradigms, opening up new possibilities for personalised, effective, and accessible learning; meanwhile, the discussion about ethical usage and bias is still growing. This study uses a knowledge mapping approach to explore the research landscape of AI in education by systematically analysing key research topics, trends, and knowledge gaps. It also discusses and explores the emerging debates on the use of AI as a “humanizer” and its impact on academic integrity. A bibliometric analysis was conducted on Scopus-indexed publications from 1976 to 2026. Network visualisation methods implemented in VOSviewer were used to examine publication growth, patterns of international collaboration, most influential studies, keyword co-occurrence patterns, and bibliographic relationships at the journal level. The results demonstrate the evolutionary nature of artificial intelligence applications all over the world from the perspectives of most cited works, collaborations among countries etc., the interdisciplinary collaborations that drive innovations, and the ethical issues associated with its implementation. This study provides a comprehensive overview of the current state of research highlighting the main trends, like countries with the most contribution in AI research in education are the USA and China, the biggest rise of AI research was seen from 2020 and 2024. However, despite the fact that AI is strongly influencing education processes, the study also discusses ethical aspects, like what should be done (and what can be at all), if a text is humanised?