The impact of artificial intelligence on business management and competitiveness

Abstract

The purpose of this study is to investigate the impact of artificial intelligence on business management and the formation of business competitiveness in the context of the digital transformation of the economy. Particular attention is paid to the analysis of AI applications in business, its role in the automation of managerial processes, business scaling, improvement of decision-making efficiency, and the creation of new sources of competitive advantage. The theoretical and methodological foundation of the research is based on contemporary concepts of digital transformation, data-driven management, and innovation-oriented business development. The study employs a combination of general scientific and specialized methods, including analysis and synthesis for systematizing scientific approaches to the understanding of artificial intelligence, a systems approach for identifying its role within enterprise management systems, comparative analysis for examining the specifics of AI implementation across different business functions, and generalization methods for identifying key trends, challenges, and prospects related to the development of intelligent technologies. The empirical basis of the research includes recent scientific publications, analytical reports of international organizations, and findings from leading consulting companies. The study demonstrates that artificial intelligence is evolving from a tool for automating individual operations into a strategic resource for enterprise development. It has been established that the most widespread areas of AI application include managerial decision support, business analytics, marketing, human resource management, financial management, logistics, and operational management. The findings indicate that the integration of intelligent technologies contributes to higher labor productivity, more efficient resource utilization, faster information processing, and improved adaptability of enterprises to changes in the external environment. The research confirms that AI facilitates the transition toward data-driven management models and supports the development of personalized services, innovative business models, and digital platforms. It is further revealed that the rapid diffusion of generative and agent-based artificial intelligence technologies enables the automation of increasingly complex managerial functions and creates new opportunities for business scaling without proportional growth in operating costs. At the same time, the study identifies several challenges associated with AI adoption, including cybersecurity risks, data protection issues, ethical concerns, regulatory uncertainty, and labor market transformation. The findings confirm that artificial intelligence has become one of the key drivers of managerial effectiveness and sustainable business development. Its implementation enables enterprises to create new sources of value, strengthen their innovation potential, and enhance their ability to adapt to dynamic competitive environments. The study highlights that the further spread of intelligent technologies will significantly influence the transformation of business processes, organizational structures, and management approaches. Future research should focus on developing methodological frameworks for assessing the impact of AI on business performance, exploring the integration of agent-based AI systems into corporate governance, and identifying effective mechanisms for combining intelligent automation with human capital development.