A bibliometric analysis of Artificial Intelligence research in higher education policy: Trends and future directions (2020–2025)

The advent of AI-driven GPTs (Generative Pre-trained Transformers) has caused substantial transformations in higher education. This study seeks to outline significant trends, prominent authors, and nascent research trajectories through bibliometric analysis of artificial intelligence (AI) research in higher education policy from 2020 to 2025. The research obtained 254 articles from the Scopus database. Keyword co-occurrence, co authorship, and co-citation mapping were utilised to shed light on the interconnection and intellectual landscape within the subject domain. The findings indicate that “Artificial Intelligence” and “Higher Education” are the predominant themes, whereas emerging themes encompass “ChatGPT”, “Generative AI”, and “Academic Integrity”, reflecting an increasing scholarly focus on generative AI technologies and their implications for the educational sector. The paucity of policy-related terminology underscores a research shortfall in the regulatory and ethical frameworks governing the application of AI in higher education. The results of co-authorship show an imbalanced collaboration structure, while the results of co-citation show a few important authors and methodological anchors, such as Braun and Clarke (2006) and Chan (2023). The study emphasises the swift expansion and inconsistent progression of AI-related higher education policy research. To ensure that AI technologies are used in a responsible, fair, and enduring manner within higher education systems around the world, it calls for greater collaboration across fields and research that focusses on policy.