Proceedings of the International scientific and practical conference “Science, Technology and Culture: Strategies for Sustainable Development” (December 15-17, 2025) / Publisher website: www.naukainfo.com. – Krakow, Poland, 2025. – 120 p.

73 A fundamental methodological shift occurred with the emergence of AI-based Language Learning (AILL). AILL is driven by technological capacity for language content generation rather than merely its discrimination or assessment. Within this new paradigm, technology transforms into a cognitive partner capable of meaningful dialogue, adaptation, and the creation of authentic communicative scenarios. The following stages are traditionally distinguished in the periodization of AILL development: 1. Initial stage: Electronic language learning (until the 1980s). The basis is Computer-Assisted Instruction (CAI) – the use of a computer as a simulator for automating exercises, reinforcing grammatical structures, and vocabulary. The communicative aspect was minimal. 2. Classic CALL (1980s–1990s). Transition from training programs to communicative CALL. Use of multimedia, interactive dialogues, and hypertexts (Hot Potatoes, Tell Me More, Rosetta Stone). 3. Intelligent CALL (ICALL, 1990–2010). Integration of first-generation artificial intelligence elements (expert systems, NLP). Adaptive exercises, error analysis, and writing assessment systems (AutoTutor, ALEKS) appear. 4. Mobile and network learning (2010–2020). The spread of mobile applications and social networks (Duolingo, Memrise). 5. AI-based Language Learning (AILL, 2020–present). Use of generative AI (LLM, ChatGPT, Claude). Models capable of conducting dialogue, creating adaptive scenarios, and acting as cognitive partners (ChatGPT, ELSA Speak, GrammarlyGO). From a pedagogical point of view, the use of LLMs offers a lot of advantages. First, they personalize the learning process by automatically adapting tasks to the student's level and learning style. Second, LLMs provide instant feedback, which helps correct speech behavior in real time. Third, the generative nature of the models allows for the creation of a large amount of authentic learning content, which significantly expands learning resources. Interactivity and the ability to simulate communication scenarios ensure the development of all language skills - speaking, writing, listening, and reading.