The coronavirus pandemic and the economic crisis in 2020 are accelerating digital transformation. During and after the crisis, there are opportunities and needs for remote work facilities, online services, delivery drones, etc. We discuss how unmanned technologies can cause a long‐term employment decrease, and why compensation mechanisms may not work. Using internationally comparable Frey‐Osborne methodology, we estimated that less than a third of employees in Russia work in professions with a high automation probability. These professions can suffer the most during quarantine measures; employment in traditional services can be significantly reduced. Till 2030, about half of the jobs in the world and a little less in Russia need to adapt during fourth industrial revolution because they are engaged in routine, potentially automated activities. In the regions, specializing in manufacturing, this value is higher; the lowest risk is in the largest agglomerations with a high share of digital economy, greater and diverse labour markets. Accelerating technological change can lead to a long‐term mismatch between the exponential increase in automation rate, compensating effects of retraining and new jobs creation. Some people will not be ready for a life‐long learning and competition with robots, and accordingly there is a possibility of their technological exclusion. The term ‘nescience economy’ and corresponding assessment method were proposed. Using an econometric model, we identified factors that reduce these risks: human capital, business climate, quality of life and ICT development. Based on these factors, some recommendations for authorities were proposed in the conclusion.

The implementation of new automation technologies together with the development of artificial intelligence can free up a significant amount of labor. This sharply increases the risks of digital transformation. At the same time, certain regions and cities differ greatly in their ability to adapt to future changes. In this article, we seek to determine the capabilities of Russian regions to reduce risks and adapt to digital transformation. The literature stipulates that there are several factors able to reduce these risks. First of all, they are associated with retraining, ICT and STEAM-technologies’ development, the promotion of economic activities that are less subject to automation. As a result of econometric calculations, we identified several factors that contribute to the new industries’ development (in our case, ICT development), and, accordingly, increase regional adaptivity. These factors include diversification, the concentration of human capital, favorable entrepreneurship conditions, the creative potential of residents, and the development of ICT infrastructure. We identified several regions with high social risks and low adaptivity, which are mainly the poorly developed regions of southern Russia, where entrepreneurial risks are high, STEAM specialists are not trained, shadow economy is large. This work contributes policy tools for adaptation to digital transformation.

Despite many governmental support programs, the entrepreneurship development in Russia is still very uneven. In this article we analyze numerous studies on entrepreneurship and find out that the institutional background in general and in certain regions is very important for the development of entrepreneurship. The risks of doing business, the complexity and duration of administrative procedures, access to capital, regulation and informal community norms are of extreme importance. The aim of this paper is to identify regional institutional factors for the development of small enterprises in Russia. With the help of the proposed econometric model we show that high investment risks and large number of economic crimes are significant deterrents for the entrepreneurial activity in Russia. The banking services’ availability and the proximity of large markets, combined with the human capital concentration, contribute to the entrepreneurship development. The impact of state support turned out to be not significant. We formulate some policy advice for entrepreneurship support in Russia.

The demand for digital technologies has been growing due to a shift in the technological and economic paradigm. The need for online services has increased since the beginning of the COVID pandemic. There are significant disparities between Russian regions in the digital technology accessibility and the development of computer skills. In 2020, the Internet diffused rapidly in most regions, although previously, there had been a slowdown. As markets got saturated with digital services, the digital divide between Russian regions narrowed. Overall, the Internet use patterns are consistent with those of the spatial diffusion of innovations. Amongst the leaders, there are regions home to the largest agglomerations and northern territories of Russia, whereas those having a high proportion of rural population lag behind. Coastal and border regions (St. Petersburg, the Kaliningrad region, Karelia, Primorsky Krai, etc.) have better access to the Internet due to their proximity to the centres of technological innovations as well as the high intensity of external relations. Leading regions have an impact on their neighbours through spatial diffusion. Econometrically, access to the Internet depends on income, the average age and level of education, and its use depends on the business climate and Internet accessibility factors. Regional markets are gradually getting more saturated with digital services and technologies. The difference between regions in terms of access to the Internet is twofold, whereas, in terms of digital technology use, the gap is manifold. In many regions, the share of online commerce, which became the driver of economic development during the lockdown, is minimal. Based on the results of the study, several recommendations have been formulated.