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The purpose of the research is to study the consequences of total (comprehensive) automatization of entrepreneurship for interested parties through the prism of competition human and artificial intellectual capital in production and distribution in Industry 4.0.

The research is conducted with application of scenario analysis, regression analysis, imitation modeling, forecasting and non-linear multi-parametric optimization with the simplex method.

The authors perform scenario modeling of competition between human and artificial intellectual capital in production and distribution in Industry 4.0 and offer recommendations for pro-active management of competition between human and artificial intellectual capital in production and distribution in Industry 4.0.

Contrary to the existing approach to studying competition between human and artificial intellectual capital in Industry 4.0, automatization of distribution, not production, is most preferable. This shows increase of the value of human intellectual capital in distribution during its automatization based on AI. This is an unprecedented and breakthrough conclusion for the modern economic science. It allows creating a completely new direction of research of competition between human and artificial intellectual capital in production and distribution in Industry 4.0, in which optimization of social consequences is achieved not by means of restraint of automatization but by means of its stimulation. The key condition is stimulation of automatization of distribution with limited automatization of production. Based on this conclusion, it is recommended to continue research in continuation of the presented work.

The purpose of this chapter is to compile the expected scenarios of development of digital economy in modern Russia and determine the essence and peculiarities of the optimal scenario implementation.

The research is based on the Theory of Games, which is used for comparison of expected scenarios of development of digital economy in modern Russia. A criterion of optimality of the scenario of development of digital economy in modern Russia in this work is effectiveness of its implementation, determined by comparing the results and expenditures in view of probability of each possible sub-scenario.

The performed scenario analysis of development of digital economy in modern Russia showed that the most effective and, therefore, optimal scenario is the one that envisages implementation of the offered new model of a well-balanced digital economy. Despite the fact that probability was determined only for sub-scenarios, within each distinguished scenario, (for determining confidence intervals of the values of indicators) which were not compared with the level of their probability, the given optimal scenario envisages the largest changes compared to the current set course of the formation of digital economy in Russia and hence is the least probable.

The established optimal expected scenario of development of digital economy, which envisages application of its new well-balanced model, is recommended for practical implementation in modern Russia. The given quantitative characteristics of the optimal scenario of development of digital economy in modern Russia could and should be recommended for usage as the basis for developing practical recommendations for monitoring and control of implementation of the optimization model of digital economy in modern Russia.

The purpose of the chapter is to study the possibilities of systemic intellectual support for managerial decisions in modern business systems and perspectives of authomatization of this process on the basis of intellectual technologies.

The methodology of the chapter includes the methods of systemic and problem analysis, analysis of causal connections, modeling, and formalization.

Advantages of usage of technologies of intellectual support for decisions in modern business systems are substantiated; they are connected to multitask character, full determination of possibilities and problems of the business system regardless of employees’ involvement in this process, and “scale effect” during making of managerial decisions. Also, drawbacks of intellectual support for decision-making in modern business systems are determined: incompleteness of authomatization of the process of making of managerial decision, foundation primarily on digital data, necessity for complex digitization of the business system, and the problem of security of digital data and intellectual technologies.

Large opportunities of systemic intellectual support for managerial decisions in modern business systems and wide perspectives of almost full authomatization of this process on the basis of intellectual technologies, accessible at all stages of the process of decision-making, are determined. For this, an algorithm of complex intellectual support for decisions in a modern business system is offered. The obtained results allow determining intellectual technologies of support for managerial decisions in modern business systems as a perspective direction of improving this process.