Survey: 66% of Lecturers and Researchers in Russia Use AI in Their Work

At universities, AI is no longer seen as an experimental technology. Lecturers integrate AI into their professional tasks: 54% use it mostly to process texts and images, 52% – to generate tasks, cases, and tests, 45% – to make presentations and visualize information, and 32% – to automate administrative tasks, such as compiling schedules or official emails. In IT and engineering, AI is also used to work with code: to generate and polish solutions. The respondents noted that they delegate routine tasks to AI, dedicating the freed-up time to research, analytical, or methodology work.

AI has proven useful in research as well. It’s most commonly used to analyze and search for literature (69%), work with texts (56%), and process and visualize data (47%). A part of respondents use AI in more specialized tasks: from developing new materials and chemical compounds to social, economic, or humanities modeling. Among the benefits of using AI, the respondents note that it helps to navigate new topics, collect primary bibliography, and note current trends; however, the researchers verify the sources, read the original papers, and interpret the results on their own.

Moreover, the respondents shared that they would like to learn more about successful cases of using AI in research and education. There is also a demand for new specialized solutions for education, particularly for tools that can generate problems with given parameters, personalize the learning process, and create tests with detailed feedback. The majority (62%) of respondents learned to use AI tools on their own, with only 38% undergoing relevant education. A third of respondents expect universities to support the integration of AI into their work processes.

“In our study, we focused on the user experience of scientists from different universities, regions, and fields – from linguistics and archaeology to mathematics and natural sciences. Particularly valuable was the diversity of perspectives: among the respondents were those who approach neural networks with cautious skepticism, as well as those who have experienced some disappointment, but many respondents are already happily integrating AI tools into their daily work. It was precisely this spectrum of opinions that allowed us to obtain a comprehensive and truly useful picture for understanding the current situation,” shared Elena Katernyuk, the study’s curator, an analyst at ITMO’s Center for Science Communication.

The study included 16 Russian universities: ITMO, Lomonosov Moscow State University, HSE University, Moscow Institute of Physics and Technology, Novosibirsk State University, St. Petersburg State University, Peter the Great St. Petersburg Polytechnic University, Kazan Federal University, Siberian Federal University, Ural Federal University, National University of Science and Technology MISiS, European University at St. Petersburg, Yaroslavl State University, Don State Technical University, Kamchatka State University, and Moscow City Pedagogical University. The methods included a survey, interviews, and focus groups. In total, 150 lecturers in engineering, natural sciences, humanities, social sciences, and interdisciplinary studies were included in the sample. The participants’ level of familiarity with AI varied from beginner to advanced.

The main focus was on AI services and products, such as digital services or software based on ML algorithms or generative models.