The integration of Artificial Intelligence (AI) into peer learning has gained significant attention with demonstrated benefits in offering an overview of student characteristics, learning environment conditions, learning processes, learning outcomes, and their interplay constituting AI-supported peer learning remains lacking. This systematic review synthesises findings from 26 empirical studies published between 2010 and 2024, identified through rigorous searches in PsychInfo, ERIC, Education Research Complete, Web of Science, and Scopus databases, following a PRISMA-guided methodology. Building on Biggs’s 3P model, the review examines student characteristics, learning environment conditions, peer learning processes, and learning outcomes in the AI-driven peer learning context. The findings underscore AI’s potential to transform peer learning through responsive and adaptive interventions while addressing challenges like over-reliance and didactical design. This review offers actionable insights for scholars and educators to guide effective AI integration in peer learning settings.
