GENERATIVE AI AS A TOOL FOR THE DEVELOPMENT OF MEDICAL ENGLISH COMMUNICATION

Abstract

The article examines generative artificial intelligence as a tool for the development of Medical English communication in the professional training of future healthcare specialists. The relevance of the study is determined by the growing role of English in academic, professional, and clinical interaction, as well as by the rapid integration of generative AI into contemporary educational practice. In medical education, English functions not only as a means of accessing scientific information, but also as an important instrument of international professional communication, academic writing, patient-oriented interaction, and clinically relevant dialogue. Therefore, the use of generative AI in Medical English learning requires purposeful pedagogical analysis.
The scientific and practical problem addressed in the article is the need to determine not only the general educational value of generative AI, but also the didactic functions of selected AI tools in developing academic, professional, and clinically oriented communicative skills of medical students. The aim of the article is to provide a theoretical substantiation and an author-based functional analysis of the didactic potential of generative AI in the development of Medical English communication. The materials of the study include recent English-language scholarly publications devoted to the use of generative AI in English language learning, professionally oriented foreign language training, and medical education. The research methods include analysis, comparison, systematization, generalization, and synthesis of scientific sources, as well as an author-designed functional and didactic analysis of selected AI tools: ChatGPT, Microsoft Copilot, Google Gemini, Claude, Perplexity AI, Elicit, Grammarly/DeepL Write.
The study has shown that generative AI can support several key dimensions of Medical English communication. These include academic writing, oral communication, medical terminology acquisition, preparation of patient-oriented texts, and the modelling of professionally significant communicative situations. ChatGPT, Gemini, Copilot, and Claude may be used for generating dialogues, case-based tasks, explanations of medical terms, role-play scenarios, and structured written assignments. Perplexity AI and Elicit are useful for searching, summarizing, and critically processing scholarly information, while Grammarly and DeepL Write can support linguistic accuracy, clarity, and stylistic improvement of English texts.
The results indicate that the didactic potential of generative AI lies not only in correcting language errors, but also in improving the structure, logic, coherence, communicative appropriateness, and professional relevance of students’ English-language output. At the same time, its effectiveness depends on instructional design, teacher guidance, critical verification of AI-generated content, academic integrity, and the balanced combination of technological and traditional forms of learning. It has been concluded that generative AI should be regarded as a promising pedagogical resource that can enhance Medical English communication when it is integrated into the educational process in a methodologically grounded, and professionally oriented way.