researcher of the Istok Center for Applied Linguistic Research and Testing, senior lecturer of Foreign Languages Department
научный сотрудник Центра прикладных лингвистических исследований и тестирования «Исток», старший преподаватель департамента иностранных языков
senior methodologist of Foreign Languages Department
старший методист департамента иностранных языков
The rapid diffusion of generative artificial intelligence (AI) is shaping a distinctive mode of technological adoption within Russian higher education, conceptualized in this article as "shadow adaptation" – a spontaneous, predominantly bottom-up integration of AI that unfolds under conditions of insufficient institutional certainty and is marked by disciplinary asymmetry. This phenomenon is linked to legal gaps, a methodological vacuum, and specific infrastructural constraints, namely difficulties surrounding the institutional use of advanced foreign models and the lack of competitive domestic solutions within the university environment. In addition, institutional uncertainty and considerable variability in pedagogical practice can also be observed. An empirical examination of several components of this concept was conducted through a survey of Russian university instructors (N = 177). The results highlight the key features of shadow adaptation: widespread yet fragmented AI use (59,3%); disciplinary asymmetry (humanities instructors use AI in their teaching more frequently than their counterparts in technical disciplines: χ² = 11,9, p < 0,001); a substantial training gap (47% of respondents had received no training in AI use for teaching); and the predominance of foreign over domestic tools, which allows this adaptation process to be interpreted as unfolding largely within a "grey" infrastructural zone. The study also describes what we provisionally term "uneven enforcement" – a lack of consistent pedagogical responses to student AI use. At the same time, no statistically significant differences in these responses were found between instructors with differing levels of personal AI-use experience (p = 0,347). The article recommends developing professional development programmes grounded in the principles of the Unified Theory of Acceptance and Use of Technology (UTAUT), with an emphasis on demonstrating the practical usefulness of AI and strengthening horizontal exchange of experience. It also underscores the need for more consistent institutional approaches to regulating AI use, as well as for assessment formats that allow for varying degrees of permissible AI involvement by students. Such measures may support a transition from spontaneous adoption to a more structured and ethically sustainable educational process.
Стремительное распространение генеративного искусственного интеллекта (ИИ) формирует в российской высшей школе особый тип освоения технологий, который в статье предлагается обозначить как «теневая адаптация» – процесс стихийного, преимущественно низового внедрения ИИ, который протекает в условиях недостаточной институциональной определённости и характеризуется дисциплинарной асимметрией.