The technological breakthrough marked by the emergence of large language models (LLMs) and their wide integration into various spheres of public life seems to have brought about a paradigmatic shift in the education system. Recent years saw a rapid development of digital technologies, however, the status of digital tools in the classroom was not to be doubted – they still function as useful assistants helping to achieve expected outcomes faster, more efficiently and in a more convenient manner. When it comes to LLMs and artificial intelligence (AI) tools, the status of teachers’ assistants does not seem to be enough to describe their place in the educational process as they have approached the role of subjects responsible for learning management.

Since most LLMs and AI-powered tools function as dialog systems, their integration into the educational process is especially fast in language teaching. There is a growing body of literature discussing various aspects of implementing AI technologies in the language classroom. Researchers focus on such areas as teaching methods, assessment strategies, and policy-making (Alshumaimeri & Alshememry 2023; AlTwijri & Alghizzi 2024; Bin Hadi et al. 2023). The universal vector for research in this field delves into human-AI interaction and collaboration in language education (Amin 2023; Su et al. 2023). Recent studies have also explored teachers’ prospects and students’ expectations related to implementation of AI technologies (Bedington et al. 2024, Chan & Hu 2023; Godwin-Jones 2022). Of particular relevance to this study are works examining regional contexts and different education levels (see, for instance, Abdalgane & Othman 2023; Alhalangy & AbdAlgane 2023; Dai et al. 2023; Imra & Almusharraf 2023).

A brief literature review makes it evident that most existing research on employing AI tools in the language classroom focuses mostly on benefits and challenges of AI integration in language teaching as seen by educators and suffers from a lack of empirical data representing students’ perspectives and analysis correlating educators’ efforts and students’ expectations. Another gap is related to regional specifics. Most available research on applying AI technologies in language education relies on Western and Asian contexts as, according to Statista (Statista.com), these regions have the largest markets for AI technologies. Recent literature on AI in education also proves this trend.

This paper aims to address both gaps and evaluate transformative potential of AI tools in language education in Russia. The study focuses on AI-initiated transformations in language teaching and aims to predict the future of language education in Russia relying on the analysis of current trends and tendencies. By examining both analytical and empirical data and employing both educators and students as respondents, the study seeks to offer insights into AI-inspired transformations in language education specifically with the context of Russian universities.

The study aims to answer the following research questions:

1. How do language educators in Russia perceive potential benefits and challenges of AI integration in language education? What are the implications of these perceptions for language teaching practices at the university level?
2. What is the role of AI in improving language learning experience at the university level?  What is the impact of AI integration into language education as perceived by Russian students?

The paper presents a qualitative study with a mixed-methods approach. It employs both analytical and empirical data to examine current trends in implementing AI-powered tools and technologies in language education. Analytical data for this study was obtained from open resources, such as analytical and statistical reports prepared by Digital Education Council, various research centers, Russia’s Higher School of Economics, etc. Empirical data objectifying perceptions of language instructors was collected from semi-structured interviews with language educators from Moscow City University and other Russian universities who were enrolled in an online professional training course on AI tools, technologies and practices in language education during the 2024/2025 academic year. The body of respondents included faculty representing various age and academic qualification groups. Empirical data reflecting perceptions of students was obtained in the course of focus group sessions with students, from pre-course and post-course questionnaires and follow-up reflexive essays. The student body included third-year bachelor students majoring in Linguistics and Translation Studies and working with English, Chinese, Japanese, and Korean languages. The students attended an optional course on digital and network technologies in language education in their third year on the translator training program and took part in the study as part of their course work.

As we live in an era where technology defines educational paradigms, it is important that researchers examine all factors leading to AI-driven transformations of the language education system in order to predict how technology can reshape current teaching approaches and practices. Our findings indicate that while Russian stakeholders are interested in AI integration into language education, at present, the spread of AI-powered tools and technologies is generally lower than in other parts of the world, for instance, in Asian and Arab states. This can be explained by limited financial support and a lack of AI literacy among students and faculty. As we also explore perceptions of all parties to the education process, there is a certain discrepancy between instructors’ and students’ perceptions of AI potential in language education. While students generally demonstrate positive attitudes and preparedness to integrate technological innovations into their learning process, instructors are less enthusiastic about such prospects. The results suggest that while there is a certain resistance against AI technologies in the language classroom, the paradigmatic shift has already started, and AI transformation of language education is inevitable. As the role of AI is increasingly becoming more significant, this process will trigger changes in the role of the language instructor who will be focused more on creative tasks while LLMs and chatbots will be responsible for generating study content. At the university level, this will allow developing more individualized courses adapted to students’ competence level and professional needs.

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