Artificial Intelligence in Dental Education: Overview of Teaching, Assessment and Academic Performance Prediction

Artificial Intelligence (AI) is increasingly used in dental education. The present study aimed to examine the current landscape of AI applications in dental education, focusing on their impact on teaching, assessment, and the prediction of academic performance. A literature search was performed based on articles published between November 2014 and March 2026 in the PubMed and Scopus databases. Studies focusing on AI applications in dental education were analysed across the domains: teaching and learning, assessment, and academic performance prediction. Forty-two publications met the inclusion criteria and were used as the evidential basis for this study. AI integration emphasised fundamental knowledge, use cases, and evaluation in teaching and learning. AI tools such as chatbots, simulations, and generative models enhanced student engagement and learning efficiency while supporting clinical decision-making. AI-assisted tasks, including radiograph interpretation and scientific writing, demonstrated improved outcomes. For assessment, AI showed moderate to high correlations with human evaluators for essay grading and thematic analysis. Further, AI models could forecast student outcomes, supporting personalised learning strategies and early intervention. AI applications have a vast potential to enhance dental education, particularly in improving teaching efficiency, personalised learning, self-directed learning, and assessment accuracy. Curriculum revisions and faculty training are necessary to fully integrate AI responsibly, leveraging its capabilities while maintaining the critical role of human oversight in education.