The use of artificial intelligence in English language teaching at higher education institutions: a theoretical analysis of the problem

Abstract

Background. In recent years, both domestic and international educational research has shown growing interest in the use of artificial intelligence (AI)-based tools in foreign language learning. English, which continues to serve as the primary language of academic and professional communication worldwide, requires teachers at higher education institutions (HEIs) to continuously review and update their teaching methodologies. The relevance of this topic lies in the fact that AI technologies — including large language models, adaptive learning platforms, and automatic speech recognition systems — offer significant opportunities to personalise the learning process to meet the needs of individual students, reduce teachers' routine workload, and enhance learners' motivation. The aim of this study is to provide a theoretical analysis of the pedagogical potential of AI tools in the context of English language teaching at higher education institutions, to systematize their advantages and potential risks, and to develop a theoretical model for integrating these technologies into educational practice.
Methods. The study was based on a theoretical analysis, systematisation, and synthesis of scholarly publications published by Ukrainian and international researchers between 2019 and 2025. Relevant sources were identified through searches of the Scopus, Web of Science, and Google Scholar databases. The study employed comparative analysis, classification, critical evaluation of the current state of research, and conceptual modelling to develop a theoretical model for integrating AI into the educational process.
Results. The analysis showed that AI tools have the greatest potential for developing writing skills owing to their ability to provide immediate feedback and adaptive learning support; moderate potential for reading and vocabulary building; and the least for speaking and listening skills. The main advantages and potential risks of AI integration were identified and categorised (learning personalisation, reduced language anxiety, increased opportunities for language practice, motivational effect of gamification) as well as the risks (threats to academic integrity, over-reliance on technology, uneven digital readiness of teachers, AI hallucinations). A theoretical model for integrating AI tools into the English language learning process was proposed, built on the principle of complementarity.
Conclusions. The theoretical analysis demonstrates that a thoughtful combination of established methodologies with AI services can significantly contribute to the development of students' language competence in non-language disciplines. However, the success of such integration largely depends on the teacher's willingness to consciously select tools, develop students' ability to critically evaluate AI-generated responses, and systematically enhance their own digital literacy. A promising direction for further research is the empirical verification of the proposed model within Ukrainian higher education institutions.