Authors

The article examines the opportunities and challenges of integrating generative language models into professional foreign language teaching in higher education institutions. It explores theoretical frameworks for implementing neural networks in teaching processes, practical methodologies for using AI-based tools, and approaches to personalised learning pathways within autonomous AI-based environments. Findings indicate that AI technologies increase learner motivation, accelerate the acquisition of domain-specific vocabulary, and foster analytical skills. The article analyses metacognitive and cognitive learning strategies for which it is appropriate to use the capabilities of neural networks at the current stage of their development. However, their effectiveness remains dependent on teachers’ digital literacy and students’ self-regulated learning strategies. A critical challenge is to maintain a balance between technological integration and humanistic educational values. The authors present empirical evidence from classroom implementations, demonstrating the transformative potential of LLMs (Large Language Models) for modernising professional language education. The paper contributes to ongoing discussions on how to optimise human-AI collaboration in academic settings while maintaining pedagogical integrity.