This study aims to explore emerging trends and future research directions in the integration of Artificial Intelligence (AI) for educational transformation through bibliometric analysis. The data analysed was taken from the SCOPUS database, covering 537 documents published between 1989 and 2024. The findings show a significant increase in the number of publications since 2017, reflecting the growing interest in the application of AI in education. The countries with the highest contributions were China and the United States, which also had the highest citation impact. The analysis shows that key research themes include personalised learning, adaptive learning systems, big data analytics, as well as advanced AI technologies such as machine learning and generative models (e.g., ChatGPT). In addition, the keyword co-occurrence network revealed the interdisciplinary nature of research in this area, with a strong focus on digital transformation and data-driven learning. The study also identifies significant challenges related to the digital divide and student data privacy, which need to be addressed in future broader AI implementations. The findings offer valuable insights for researchers, educators and policymakers, and provide practical recommendations to effectively utilise AI in creating inclusive and sustainable educational environments.
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