Integrating Applied Artificial Intelligence into Non-Technical Master’s Programs: Conceptual Models and Practical Approaches

The article explores the integration of applied artificial intelligence (AI) into nontechnical master’s programs, focusing on the challenges, trends, and prospects of this process. The relevance of the topic stems from the global professionalization of AI, the emergence of new professions (e.g., AI trainer, prompt engineer), and the transformation of the labor market under the influence of digital technologies. The authors emphasize the role of master’s education as a key link in training professionals capable of applying AI tools in non-technical fields – from medicine to the humanities. The research methodology includes a content analysis of job postings (on the hh.ru platform), which revealed fragmented but cross-sectoral demand for AI skills: 24% of vacancies are concentrated in creative industries (marketing, design), 20% in IT, while in medicine and education, their share does not exceed 3–5%. Job requirements in non-IT sectors remain vague, indicating a lack of standardization. A review of 78 Russian master’s programs demonstrates the dominance of technical disciplines related to applied AI (80% of programs), though a rise in interdisciplinary initiatives, such as AI in political science, philosophy, and media communications (9 socio-humanitarian programs), is noted. Key challenges include the tech-centric nature of education (programs implemented within IT fields), superficial implementation, and institutional accessibility barriers. Prospects are linked to the development of interdisciplinarity, stronger partnerships with industry leaders (Yandex, Sber), and the cultivation of ‘hybrid’ skills. The authors conclude that there is a dual asynchrony between the labor market and universities regarding the integration of applied AI skills. The article contributes to the discourse on the digital transformation of education.

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