Diversification of educational services in the conditions of industry 4.0 on the basis of AI training

Abstract

Purpose The purpose of the paper is to determine the perspectives of diversification of educational services in the conditions of industry 4.0 on the basis of artificial intelligence (AI) training, determine the consequences of this process for academic and teaching staff and to develop recommendations for its practical implementation. Design/methodology/approach The methods of horizontal, trends and regression analysis are used for studying social consequences of digital modernization of the markets of higher education (for academic and teaching staff). The research is performed by the example of modern Russia on the basis of the statistical data of Federal State Statistics Service and the International Telecommunication Union. The timeframe of the research covers academic years 2000/2001-2018/2019. Findings It is determined that digital modernization of the sphere of higher education stimulates the reduction of the universities’ need for academic and teaching staff and growth of their unemployment. However, further digital modernization of economy on the basis of breakthrough technologies of industry 4.0 will lead to creation of a new type of educational services that are provided within entrepreneurship of universities – AI training of business. This will ensure development of university entrepreneurship (and reduction of dependence of universities on state financing), as well as growth of the employment opportunities for experts (academic and teaching staff) in the sphere of AI, which will not depend on the number of students, but will be connected to demand for AI training from digital business. Originality/value The role of AI training in the structure of production business processes of a university in the conditions of industry 4.0 is determined. The necessity for state stimulation of development of digital business in the modern economic systems is substantiated. It is shown that government has to pay close attention to the issues of support in the sphere of AI and mass distribution of their results. Because of this, it will be possible to control social risks in the sphere of higher education.