Abstract

The article is devoted to the study of the impact of artificial intelligence on employment in businesses. Recent advances in natural language processing and recognition, machine learning platforms and AI-optimized hardware, as well as free access to these technologies, have created an urgent need to implement them in business to ensure high results in financial and economic activities. The study presents the prerequisites that formed the basis for the formation and development of a new era of AI automation. The scientific achievements and conclusions of international companies regarding the role of artificial intelligence in the global economy are analyzed, and the trends in its use by organizations at different levels of management are revealed. The authors characterize the methods of automation of various types of work at an enterprise with the use of the technologies under study and the impact of the process on employment and wages. It is found that today the greatest impact is the recovery effect, based on which conclusions are drawn about the need for synergy of human and machine labor, rather than their separate functioning. The reasons for the attractiveness of AI automation for business are identified, and examples of their effective implementation are given. There are revealed advantages of the increasing use of technology in business: cost savings, increased revenue, increased productivity and competitiveness of companies, creativity and personalization, limiting the influence of the human factor on work results. The article highlights the threats of large-scale introduction of AI into business activities for employees, which include excessive control over them by employers, violation of the principles of information confidentiality, complexity and imperfection of the system, constant updating of requirements for advanced training, and the necessity to train employees to interact with intelligence. These threats can lead to employee dismissals, loss of motivation, and aggravation of social inequality and social justice issues, which will generally create a negative attitude toward the company. Based on the analysis of data sets on professions with a high risk of AI automation in various industries and the projected change in demand for them, the authors reveal a correlation between the level of threat and the complexity of tasks, the creativity involved, and the speed in decisionmaking and implementation. Finally, it is concluded that new approaches to regulating the impact of technology on the structure of employment should be applied due to its dynamic growth.

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