Translation. Region: Russian Federation –
Source: State University Higher School of Economics – State University Higher School of Economics –
Russian universities are noticeably differentiated in their training in the field of AI. More than half of all students in the AI profile are concentrated in 18 organizations that implement specialized programs and offer the most widespread and at the same time selective programs (about 4% of the surveyed organizations).
In general, the selectivity of programs in the AI profile is higher than that of programs containing a module on AI, programs in the field of information technology (IT), and bachelor’s and specialist programs in general, and this applies to most large groups of specialties and areas of training. Programs in the field of AI in mathematical and technical sciences are distinguished by increased selectivity in the selection of applicants.
A number of regions entered the leading groups (with indicator values above the Russian average) both in terms of student coverage by AI-focused programs and programs with an AI module. These include Moscow and St. Petersburg, Rostov, Vologda, Arkhangelsk, Chelyabinsk, Samara, Penza, and Moscow regions. The situation with AI technology training in the regions is directly affected by the degree of AI penetration into their economies. The inequality of opportunities for providing AI technology training is partly explained by the uneven territorial distribution of IT organizations engaged in the development of AI products. However, in a number of cases, the development of AI education significantly lags behind the level of AI implementation in the regional economy. This is due, in particular, to the use of ready-made solutions created by specialists from other constituent entities of the Russian Federation, which indicates that there is a demand for AI developments in such regions and a need to increase the training of their own personnel in the field of AI.
The provision of teachers in the field of AI in the absolute majority of the universities under consideration exceeds 90%. At the same time, the gap in the values of the indicator between the universities that train specialized specialists is not so large as to conclude that the shortage of personnel plays a key role in their differentiation by the level of development of training in the field of AI. However, attention is drawn to the significantly higher level of shortage of personnel of the appropriate qualifications in universities that do not implement specialized programs, but have included AI modules in other programs. Thus, it can be assumed that organizations with experience in implementing specialized programs have formed teams of teachers of AI disciplines, while other universities have not yet fully succeeded in solving this problem.
A specialized digital infrastructure — digital equipment and content — plays an important role in training highly qualified specialists in the field of AI. In all clusters of universities considered in the report, formed depending on the volume of training in AI-related programs, there is a shortage of digital resources, primarily in terms of computing power based on graphics accelerators, which are key for tasks related to AI. Universities with experience in training specialists in specialized programs are better provided with content than with equipment. Organizations that provide training only within the AI module are equipped with both approximately equally and, unfortunately, insufficiently.
Universities that are just beginning to master the AI field have such a pronounced deficit of the digital resources necessary for this that it practically does not allow them to develop programs in the relevant profile and significantly complicates practice-oriented training within the AI modules. The lack of specialized digital infrastructure, therefore, can be the main obstacle to the development of training of specialists in the field of AI in universities.
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