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Готовность высшего образования к внедрению искусственного интеллекта: библиометрический анализ
Objective. To identify key areas of readiness for the use of AI in higher education. Methodology and research design. The following research question was formulated: What research directions are observed in the existing discourse on readiness for the diffusion of AI technologies in higher education? To answer the research question, a bibliometric analysis was conducted on the co-citation of 2,237 publications indexed in the SCOPUS database for the period 2011-2024. Further, the study performed qualitative coding of the abstracts to narrow the sample to the 598 most relevant publications. Results. Using bibliometric analysis, five main research directions were identified: (1) formation of strategic readiness of universities for AI in educational organizations (2) formation of organizational readiness of universities for AI (3) formation of consumer readiness of teachers and students for AI (4) formation of psychological parameters of readiness for AI (5) formation of decision-making mechanisms in the implementation of AI. Conclusions. The obtained results indicate the multilevel nature of readiness for AI implementation on strategic, organizational and personal-psychological The success of AI integration into the educational environment depends not only on technological resources and regulations, but also on users' trust in algorithms, their emotional comfort and sense of personal competence.Value of results.The study is a systematic review of scientific publications using a bibliometric approach, which allows to identify new promising directions for further development of the topic of higher education readiness for AI diffusion.It contributes to the understanding of the role of AI as a key factor in the transformation of higher education.