Experts noted the importance of the partnership between universities and Bigtech in the training of AI personnel in Russia

The Russian system of training AI specialists, based on cooperation between BigTech, universities and the state, quickly adapts programs to meet market needs. This is the conclusion reached by J'son & Partners Consulting experts based on the results of the study, comparing approaches to training AI personnel in Russia, the USA and China.

The key problem for all countries is the gap between the pace of AI development and the updating of curricula. According to analysts, it takes 7-10 years for a full cycle of software adaptation, while market requirements for AI specialists are changing faster.

Each of the three countries has a different approach to the task of updating curricula. For example, in the United States, the autonomy of universities allows for the rapid introduction of new disciplines and the training of unique specialists, but the lack of uniform standards and the high cost of education (according to research, up to $60,000 per year) makes the educational system heterogeneous. In China, strict government regulation provides advantages in training mass specialists, but it turns out to be less effective in training personnel to solve complex tasks.

The Russian model, according to analysts, is characterized by high stability and suitability for long-term training of specialists. It is based on a systematic partnership between large technology companies and universities. Today, most big tech companies are involved in education, including launching joint initiatives such as AI360– an undergraduate course for AI architects launched by Sberbank and Yandex at five leading universities.

Maxim Stolpovsky, Deputy CEO of J'son & Partners Consulting, notes that the Russian BT education system is distinguished by a balance between mass graduation and the training of unique personnel.

"Thanks to it, it is possible to simultaneously meet the needs of the national economy and train AI specialists who develop artificial intelligence and related sciences, develop new architectures, models and solve other complex tasks," Stolpovsky emphasized.

Technology companies have been developing IT education for more than 10 years, long before the AI boom. Thus, the disciplines of the Yandex School of Data Analysis formed the basis of a number of programs at the Higher School of Economics, MIPT, St. Petersburg State University and other universities. By 2011, the first joint projects of companies and universities began to appear, such as Technopark VK and Bauman Moscow State Technical University. Today, most bigtechs are involved in education.

"Bigtechs set the trend and define the requirements for the skills and competencies of specialists, which then turn out to be useful for the entire economy," said Maxim Stolpovsky.

At the same time, according to experts, one of the challenges for the current system of training AI personnel in Russia is the shortage of teachers in universities. The industry partially compensates for this by inviting practitioners from technology companies to universities. Today, more than 1,200 Yandex employees, about 1,000 VK specialists and 900 from T-Bank teach at IT programs.

"Without the participation of high-quality practical teachers in the industry, graduates do not gain versatility and breadth of knowledge. Students are potential cadres of bigtech companies. Naturally, they want to participate in the training of their future specialists so that they can be taught relevant knowledge," said Roman Dushkin, head of the educational program "Artificial Intelligence and Modeling of Cognitive Processes in the Design and Development of Information Systems" at the National Research Nuclear University MEPhI.

Analysts note that the established partnership between business, universities and the state makes it possible to provide the market with AI specialists with the necessary competencies - according to analysts, today the industry needs about 200 thousand professionals.

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