The potential of artificial intelligence in the context of collaborative pedagogy

The article explores the potential of artificial intelligence (AI) in collaborative pedagogy, systematizing AI applications in higher education and aligning them with models of joint learning activities. The authors analyze AI tools through S.I. Pozdeeva's typology: task-based (authoritarian model), problem-based (leader-driven), and dialog-based (partnership) lessons. Based on a review of 94 scholarly sources and classification of 289 AI tools, 28 relevant solutions (e.g., YandexGPT, Duolingo Max) were selected. Results confirm AI's applicability to all collaborative activity types: task-based lessons: generating solution algorithms, personalizing assignments; problem-based lessons: designing solution stages, analyzing alternatives; dialog-based lessons: stimulating discussions, curating debate topics. Key AI functions include automation of routine tasks (grading, lesson planning), content generation, and personalized learning pathways. The practical contribution is a matrix integrating AI tools with pedagogical tasks and lesson typologies. Critical limitations involve risks of AI-generated inaccuracies, socioeconomic access disparities, and needed shifts in teaching methodologies. The study redefines AI's role: from an individualization tool to a facilitator of group communication and cooperation. Future research should explore AI as a conditional "subject" in educational processes. The authors declare no conflicts of interests.