Analysis of the effectiveness of the use of artificial intelligence and machine learning in the management processes of large corporations

Abstract

In recent years, there has been an exponential growth in the use of artificial intelligence (AI) and machine learning (ML) technologies in various fields, including the management of large corporations. This article addresses issues related to analyzing the effectiveness of implementing AI and ML in management processes, as well as identifying key factors influencing their successful application. The study employed data analysis methods, including comparative analysis, regression analysis, and machine learning methods. Data from various sources were collected, covering information on the use of AI and ML in large corporations. Interviews were also conducted with top managers and experts in AI and management. To assess the effectiveness of AI and ML in management processes, performance, financial results, and employee satisfaction indicators were used. The study showed that the use of AI and ML in management processes can significantly improve the productivity and efficiency of large corporations. In particular, it was found that the automation of routine tasks and the analysis of large volumes of data using AI and ML lead to reduced operational costs and increased strategic flexibility of companies. Furthermore, the application of these technologies contributes to the improvement of decision-making quality through more accurate and faster information analysis. Despite numerous advantages, the implementation of AI and ML in management processes faces several challenges, such as the need for significant investments, problems with integrating new technologies into existing processes, and resistance from employees. However, with the right approach to implementation and staff training, these challenges can be overcome, allowing the full potential of AI and ML to be realized. The application of AI and ML in the management processes of large corporations is a promising direction that can significantly enhance the efficiency and competitiveness of companies. Addressing the challenges associated with implementation requires a comprehensive and systematic approach, including investments in technology and staff training.