Generative AI and student collaboration: a scoping review of group work processes, outcomes, and risks

Abstract Generative artificial intelligence is increasingly used by higher education students during group work; however, evidence on how it reshapes collaboration remains fragmented. This scoping review maps recent research on how generative AI influences student group work in higher education and identifies the reported benefits, risks, and implications for practice. Following the PRISMA extension for scoping reviews, Scopus, Web of Science, and Google Scholar were searched for English-language publications from January 2023 to March 2025. After screening, 18 studies were included and analysed using reflexive thematic analysis. The literature reports the potential benefits of group knowledge development, idea generation, reflective thinking support, communication efficiency, task coordination, and timely feedback. Reported risks include reduced peer-to-peer interaction and critical engagement when tools are over-relied on, alongside privacy, transparency, and bias concerns in AI-mediated collaboration. Across studies, outcomes appear contingent on task design, degree of integration into group workflows, and students’ AI literacy and subject expertise. The review highlights the need for clearer pedagogical guidance on when and how generative AI should be used in group work to preserve human agency, support academic integrity and equitable participation, and align assessments with collaborative learning processes. Future research should prioritise longitudinal and intervention-based studies that examine both learning outcomes and group dynamics over time.