This paper addresses the integration of artificial intelligence (AI) into educational practices at Russian universities. It examines faculty members’ attitudes toward this process, the forms of acceptance and resistance emerging within academia, and how it shapes understandings of university teaching as a profession. It also identifies sources of risk and the social consequences of AI-driven transformation: professional inequality, deprofessionalization, and disparities in educational quality across universities. The study draws on data from a questionnaire survey of teaching and research staff (n = 298, May–June 2025) from 15 Russian universities, supplemented by responses to an initial assessment completed by participants in a continuing professional development program (n = 21). Respondents were purposively selected from among participants in digital transformation projects. The analysis found that awareness of AI technologies does not guarantee their regular use: only 50.6% of respondents reported using AI tools in their professional practice, while readiness to use them (2.93 points) significantly exceeds self-assessed competence (2.33 points). Personal experience with these technologies and subjective trust in them develop unevenly, with a substantial proportion of respondents adopting a cautious, selective approach to AI use. The findings reveal ambivalent perceptions: faculty members see AI as a means of saving time and making learning more interactive, but also as a source of risks, including a decline in the quality of students’ education, a weakening of their critical thinking, and changes in faculty members’ professional role. A comparison of the relative importance of different barriers indicates that technical and resource constraints are not the principal barriers; gaps in professional competence, pedagogical difficulties, and normative and value-based concerns about educational quality play a much greater role.

Drawing on H. Lübbe’s theories of temporal uncertainty and A. Reckwitz’s “logic of singularities,” the authors show that accelerating technological change and the algorithmization of routine functions conflict with the bureaucratic organization of teaching. Rigid educational standards and an emphasis on prescribed performance indicators hinder the development of faculty members’ distinctive competencies, turning AI integration into a conflict between technological efficiency and academic agency. The introduction of AI redefines the boundaries of routine work, expands the range of tasks that can be automated, and generates demand for nonroutine cognitive work for which faculty members are not always prepared. Consequently, introducing AI into educational practices entails not only technical and pedagogical changes but also a reconsideration of faculty members’ professional role.

artificial intelligence, higher education, academic and teaching staff, trust, professional identity

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