Automated language learning systems: Cognitive-linguistic perspectives

The ongoing transformation of language education is driven by the widespread adoption of automated language learning systems that adapt instruction to learners’ individual characteristics while enhancing motivation and interaction. The relevance of this study stems from the need to improve the quality of foreign language education in the context of societal digitalization and to assess how digital infrastructure affects the effectiveness of intelligent language platforms. The aim of the study is to clarify the relationship between the level of development of the digital educational ecosystem and the effectiveness of automated language learning systems. The methodology is based on secondary analysis of international statistical data, systematic literature reviews, and comparative analysis of scientific publications addressing the integration of artificial intelligence into foreign language teaching. The results demonstrate that a well-developed digital infrastructure significantly expands the potential of intelligent systems to foster communicative and cognitive skills, whereas low digital maturity limits their educational impact. The study proposes a conceptual view of intelligent language platforms as tools of humanistic and personalized education that enhance educational quality, promote inclusiveness, and support intercultural interaction. The practical significance lies in informing institutional digital strategies, optimizing blended and distance learning models, and improving methodological support for foreign language instruction.