Assessing the scaling potential of artificial intelligence tools in higher education: Russian and international experiences
https://doi.org/10.17853/1994-5639-2025-8-128-157
Abstract
Introduction. The relevance of this study stems from the rapid introduction of artificial intelligence (AI) technologies across various sectors of Russia’s economy and social sphere, alongside an insufficient scientific examination of the challenges involved in integrating these technologies into the higher education system. Aim. The present research aims to assess the potential use of AI technologies in Russian higher education by conducting a comparative analysis of Russian and international experiences. Methodology and research methods. The study employs a systems approach methodology. To address the tasks, a range of methods was utilised, including comparative, correlational and content analysis, systematisation of information, and rating. Results. Based on a comparative analysis of AI implementation practices at 36 universities worldwide (including 15 in Russia), five key areas of application were identified: management and analytics, adaptive learning, optimisation of teaching staff workload, organisation of the educational process, and research support. A strong correlation (r = 0.92) was found between the number of universities with successful AI implementation practices in a country and that country’s position in the Global AI Index. Scientific novelty. This is the first comparative analysis of AI implementation practices in leading universities worldwide, providing an evaluation of the technology and addressing the existing gap in scientific research on the subject. Practical significance. The results of this study can be used by universities to develop strategies for implementing AI. The identified best practices can also be employed to assess the potential of the technology in each of the specified areas of AI application.
About the Authors
D. D. Vavilova
Russian Presidential Academy of National Economy and Public Administration
Russian Federation
Russian Federation
Daiana D. Vavilova – Cand. Sci. (Engineering), Leading Researcher, Directorate of Priority Educational Initiatives
Moscow
ResearcherID AAG-7809-2019
E. V. Kasatkina
Russian Presidential Academy of National Economy and Public Administration
Russian Federation
Russian Federation
Ekaterina V. Kasatkina – Cand. Sci. (Physics and Mathematics), Associate Professor, Leading Researcher, Directorate of Priority Educational Initiatives
Moscow
ResearcherID M-6863-2016
R. V. Faizullin
Russian Presidential Academy of National Economy and Public Administration
Russian Federation
Russian Federation
Rinat V. Fayzullin – Cand. Sci. (Economics), Associate Professor, Project Director, Leading Researcher, Directorate of Priority Educational Initiatives
Moscow
ResearcherID AAC-7347-2021
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Review
For citations:
Vavilova D.D., Kasatkina E.V., Faizullin R.V. Assessing the scaling potential of artificial intelligence tools in higher education: Russian and international experiences. The Education and science journal. 2025;27(9):128-157. (In Russ.) https://doi.org/10.17853/1994-5639-2025-8-128-157
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