Generative AI and its Impact on the Development of Intercultural Competence in Linguistics Students

Aim. To observe the pedagogical potential and limitations of using generative neural networks in the process of developing intercultural competence among linguistics students. The relevance of the study is formed by urgent need to modernize foreign language teaching methodologies in response to the rapid integration of artificial intelligence technologies into educational practice. Methodology. The methodological framework of the study is based on an interdisciplinary approach that integrates the principles of three scientific traditions: the cognitive-communicative approach (M. Bennett, M. Byram), which views intercultural competence as a process of developing intercultural sensitivity and the ability to adopt an ethnorelative perspective; the linguocultural school (V. G. Kostomarov, V. V. Krasnykh, E. M. Vereshchagin), which emphasizes the correlation between language and culture and the role of background knowledge in cross-linguistic interaction; the pedagogy of the digital educational environment (I. V. Robert, E. Yu. Semago, A. V. Khutorskoy; N. Selw-yn, P. Mishra, M. Warschauer), which explores the transformation of teaching practices under the influence of intelligent technologies and digital tools. The research methods include content analysis of Al-generated texts to identify the presence or absence of culturally marked elements, case analysis of instructional scenarios involving generative neural networks for simulating intercultural communication, comparative analysis of traditional and Al-assisted instructional formats in terms of their effectiveness in developing components of intercultural competence. Results reveal both potential advantages of AI use (expansion of linguistic and cultural awareness, development of culturally marked context comprehension skills) and limitations (risk of stereotyping, insufficient depth of cultural context, lack of empathetic interpretation). Research implications. The theoretical significance consists in substantiating the role of neural network technologies as tools for developing intercultural competence. The practical value is reflected in the potential integration of AI into foreign language curricula aimed at enhancing students’ crosscultural skills. Conclusions. The use of generative neural networks in language education has a positive impact on the development of intercultural competence among linguistics students, provided that their implementation is methodologically structured and pedagogically supported. To minimize risks, a critical approach, pedagogical interpretation, and the integration of AI into the educational process within interdisciplinary programs are required.