Purpose: The purpose of this article is to determine the future proportion and variants of usage of human intellect and artificial intelligence (AI) in entrepreneurship of industry 4.0 that fits social entrepreneurship the most. It could be convergence (simultaneous utilization during the same entrepreneurial processes with the emphasis on unique features by the terms of the competition) or divergence (usage during different business processes by the terms of labor division).Design/methodology/approach: The authors determine the influence of usage of human capital and AI on the efficiency of social entrepreneurship. The authors identify the perspective directions of usage of AI in social entrepreneurship and evaluate the readiness and interest in the implementation of these directions of concerned parties. The authors also model the optimal proportions and the variant of usage of human intellect and AI in social entrepreneurship in the conditions of Industry 4.0 in the future (until 2030).Findings: It is found that social entrepreneurship will use the opportunities of Industry 4.0 for optimization of its activities until 2030, but will refuse from full automatization, using human intellect and AI at the same time.Originality/value: The most perspective directions of application of AI at social companies are a collection of social goods and services, marketing studies and promotion of social goods and services. Neither convergence nor divergence of human and artificial intellectual capital does not fully conform to the interests of concerned parties. The most preferable (optimal) variant of usage of human intellect and AI in social entrepreneurship in the Industry 4.0 is human intelligent decision support.

The paper aims to test whether corporate social responsibility (CSR) performance affects the costs of debt, equity, and a weighted average of those two components in BRICS countries. Theoretically, a decline in the cost of capital is linked to a decrease in the firm risk. We measure CSR performance using the environmental, social, and governance (ESG) combined score from the Thomson Reuters EIKON database for non‐financial enterprises between 2014 and 2019. A panel regression analysis has been run in order to test whether (1) the inclusion in the ESG combined ranking or (2) the level of the scores for ESG combines is linked to a decline in the cost of capital. Empirical evidence suggests that the level of the ESG combined score does not affect the firm's financial risk. Inclusion in the ESG combined index decreases the cost of equity and the average cost of capital instead. Firms that received an ESG combined score pay lower returns to investors.