Keyword: «international economists»

The relevance of the study is driven by the global digital transformation of economic systems and the emergence of a new technological paradigm, which leads to stricter requirements for the level of professional foreign language proficiency among specialists in the field of international economic relations. A contradiction has emerged: on the one hand, the labour market is in dire need of economists capable of effective foreign language communication in a digital environment; on the other hand, the didactic resources of artificial intelligence technologies for solving this problem remain insufficiently studied. The cognitive characteristics of the modern “digital generation” of students, whose educational expectations and ways of processing information differ significantly from those of the past, add further urgency to the issue. The aim of the article is to identify, structure, and characterise the didactic potential of applying artificial intelligence technologies in the process of professional language training of future international economists through a comprehensive analysis. The methodological basis of the work includes methods of theoretical analysis of Russian and foreign scientific-pedagogical literature, as well as systematisation of AI-based digital tools relevant for language education in economic universities. The results of the study theoretically substantiate the feasibility of integrating AI technologies into the practice of professionally oriented foreign language teaching. The didactic potential of these technologies is systematised in five areas: using interactive formats (chatbots, voice assistants) to increase learning motivation; applying algorithmic spaced repetition for effective acquisition of professional vocabulary; modelling authentic professional situations and cases using generative neural networks (ChatGPT, BloombergGPT, Finprophet); designing individual educational trajectories based on adaptive algorithms; and organising instant evaluative feedback that overcomes the shortcomings of traditional assessment methods. In addition, a classification is developed and proposed that includes six types of feedback generated by AI tools: educational social, informational referential, methodological, analytical, evaluative, and conditionally creative. Each type is associated with specific digital services and neural network solutions. The theoretical significance of the work lies in deepening scientific understanding of the mechanisms and principles of integrating AI technologies into the context of professionally oriented foreign language education. The practical significance consists in the development of comprehensive recommendations and specific examples of using AI tools, which can be directly implemented into the curricula of economic universities to improve the effectiveness of forming professional and communicative competences of future specialists.