Abstract
<jats:p>Given the global interest in Russian as a foreign language (RFL) and the rapid development of digital technologies, there is a need for pedagogical models focused not on knowledge transfer, but on managing learners’ cognitive processes. This article provides a theoretical justification for the integration of artificial intelligence (AI) into the cognitive-didactic paradigm of teaching Russian as a foreign language. The aim of the study is to demonstrate how AI can be methodologically correctly integrated into the educational process to improve the effectiveness of language acquisition through personalization, optimization of cognitive load, and support for the formation of stable mental representations. Based on a synthesis of the principles of cognitive linguodidactics,the author proposes the theory of the zone of proximal development (L.S. Vygotsky), and the theory of cognitive load (J. Sweller), a conceptual model of the student-AI-teacher interaction. In this triad, AI acts not as a substitute for the teacher, but as a cognitive support tool implementing four key functions: adaptive presentation of material, intelligent training that takes into account individual errors, the generation of immersive communicative environments, and the development of the student’s metacognitive strategies. The article pays particular attention to aspects of the Russian language that are difficult for foreign students-the case system and verb pairing-where AI provides a step-by-step, contextualized introduction of material in the zone of proximal development. The work emphasizes that the effectiveness of adaptive technologies depends on the linguodidactic foundation of AI systems, while the teacher retains a leading role in designing and adjusting individual learning trajectories.</jats:p>