THEORETICAL AND FUNDAMENTAL DIRECTIONS OF APPLYING ARTIFICIAL INTELLIGENCE IN INDUSTRIAL ENTERPRISE MANAGEMENT

Abstract

The purpose of this study is to analyze the theoretical and fundamental directions of applying artificial intelligence in the management of industrial enterprises and to identify its role in improving managerial efficiency, decision-making quality, and organizational adaptability under conditions of digital transformation. The research is based on a qualitative methodological approach, including systematic literature review, conceptual and comparative analysis, and synthesis of contemporary theories related to artificial intelligence, industrial management, and Industry 4.0. Scientific publications indexed in Scopus and Web of Science, as well as analytical reports of international organizations, were used as the main information sources. The study systematizes the key theoretical foundations and fundamental directions of artificial intelligence application in industrial enterprise management, including strategic planning, decision support systems, resource optimization, risk management, and performance evaluation. The results show that artificial intelligence enables the transition from traditional management models to intelligent, data-driven, and adaptive management systems, significantly enhancing operational efficiency and managerial responsiveness. The research concludes that artificial intelligence represents a strategic management resource rather than merely a technological tool. The theoretical contribution of the study lies in developing a conceptual framework for integrating artificial intelligence into industrial management processes. The findings provide a theoretical basis for further empirical research and practical implementation of intelligent management systems in industrial enterprises.