Teachers’ Integration of Artificial Intelligence in Education: A Systematic Review of Applications and Outcomes

Abstract

Artificial intelligence (AI) is increasingly shaping teaching practices across diverse educational contexts. However, the existing literature remains fragmented, with limited consensus on how teachers use AI, the contexts in which it is employed, and its implications for teaching and learning. This systematic review synthesizes research published between 2016 and 2025 to examine the use and integration of AI in teaching practices, with particular attention to the educational levels, disciplines, AI modalities, pedagogical applications, and reported learning-related outcomes. Following PRISMA guidelines, 100 articles were identified and analyzed. The findings indicated an imbalance in research trends within the field. Most investigations examined the pedagogical integration of various AI technologies in teaching, including AI-based conversational systems, intelligent assessment and learning systems, extended reality technologies, auditory-visual computing systems, and educational analytics for learning and teaching. Integrating AI in teaching was mainly focused on the higher education context, which accounted for 50% of all the selected articles. Regarding disciplinary focus, English language education (21,6%) and computer science (18,3%) dominated teachers’ integration of AI into teaching. The study emphasized the significance of expanding future research on AI-supported professional development and AI literacy while also examining AI integration from both instructional and learner-centered perspectives. Future research should also examine technological limitations and ethical concerns to promote the effective use of AI in education.