Artificial intelligence tools for managing the behavior of economic agents at micro level

Abstract

In modern business conditions, effective management of employee behavior is becoming a critical factor in ensuring competitive advantages and development of enterprises. AI tools, which are rapidly developing, provide new opportunities for managing the behavior of economic agents at the micro level and increasing the productivity of companies. To make the most effective use of AI in the outlined processes, there is a need to conduct research into the areas and possibilities of their application and impact on enterprise personnel. The methodology and mathematical model developed in the article, based on the use of theories of fuzzy sets, neural networks and Lefebvre reflexive control, allow to study the potential and prospects for using AI tools (on an example of SAP SuccessFactors) in managing the behavior of economic agents at the micro level, in particular in predicting the efficiency of employees at enterprise. It was concluded that the SAP SuccessFactors can evaluate the effectiveness of various personnel groups differently. This may occur due to insufficient adaptation of the models to the specifics of work and personal characteristics of employees of different productivity levels. Therefore, when using AI tools in the management of personnel behavior, it is important to consider such features and make individual settings for different groups of employee performance. This is a key aspect to avoid wrong management decisions that can affect the economic efficiency of the enterprise.