The study uses the statistical method, the method of analogy and comparison, as well as the positive and normative approach. Findings: The study indicated that in the agricultural sector there are several problems associated with the formation of human resources. This is evidenced by the presence of negative trends that have been observed over the past 20 years. The main problems are the low educational level of workers, aging professional staff, and a reduction in the number of employees in all positions. Practical implications: The socioeconomic problems considered in the article indicate the urgent need to develop a mechanism of state support for agricultural workers. Originality/Value: The authors define the concept of human capital and reveal the essence of the factors influencing its formation, revealing them from the perspective of the socioeconomic development of the region.
This article discusses the impact of artificial intelligence in human resource management in a market economy. The aim of the article is to study the main modern trends in the development and transformation of human resource management systems under the influence of artificial intelligence. It has been established that the use of artificial intelligence (AI) carries both advantages and threats, which requires the modern economic paradigm of being ready for the challenges of digitalization, the possibility of a quick transition to realizing the use of human creative abilities and creating the conditions for a qualitative transformation of the educational sector and labor market. In addition, the use of AI will allow to achieve positive results if clear tasks are formulated before him, and, conversely, it turns out to be unable to fulfill its goals in conditions of uncertainty.
Subject/Topic. The article is devoted to the study of the possibilities and threats of using scientific intelligence in the business foresight and its impact on the business potential of the business in the short and long term. Methodology. In the process of writing the article, general scientific and philosophical methods of knowledge were used, as well as special economic methods based on them. Especially, the articles of the object of research – artificial intelligence – as the current process necessitated the use of problem-chronological and historical-genetic methods, which made it possible to distinguish the main stages of the formation of ideas, concepts, theories and methods for the use of artificial intelligence in business foresight, and the historical-genetic method showed the inseparability and intersectability from one stage to another of the development of the conceptual and methodological apparatus of the object of scientific research. Results. Currently, in business practice, artificial intelligence is used as a foresight tool very individually, since the complexity of its development and significant investments in the landscape infrastructure of its functioning form objective barriers to its rapid spread in the business environment. Currently, the following models of artificial intelligence are used in the business force: anthropocentric, hybrid, instrumental, machine-centric. According to the above calculations, starting from 2020, active growth is expected in the segment of business and IT services using artificial intelligence, it is also expected to increase spending on R&D projects in the field of development of products with artificial intelligence, and the most forward-specific from the point of view of investing capital and development as part of their own business model of AI directions on the horizon 2018-2025 are technologies for remote access (VDI, BKC, online communications, control), AI/ML (artificial intelligence, machine learning), VR/AR (virtual and augmented reality). Conclusions/Significance. In general, in 2020 compared to 2019, the optimism and motivation of the business to introduce artificial intelligence clearly showed a decline, and it should also be noted that the goals set by managers have become more «grounded»: in 2020, 45% spoke in favor of using artificial intelligence as a means of forming their own Big Data libraries, another 45% – for the integration of the artificial intelligence mechanism and existing systems for analysis and collection of information, however, a modern business strategy is not possible without processing huge amounts of customer information, and given their weak structuring and localization in multiple sources, the speed and quality of their processing and interpretation without the use of machine learning mechanisms became economically impractical. Application. The results of the scientific research will be useful both for educational purposes for students and readers interested in the use of artificial in-tech in business management, and for practitioners who plan to use artificial intelligence in foresight business processes.
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