ARTIFICIAL INTELLIGENCE AS A TOOL FOR RISK MANAGEMENT AND ENHANCING ENTERPRISE COMPETITIVENESS

Abstract

In modern conditions of global digitalization and the relentless increase in external environmental uncertainty , enterprises face a complex set of risks that significantly complicate the process of achieving strategic goals. This creates an objective necessity to introduce new, digitally oriented management approaches , among which Artificial Intelligence (AI) systems occupy a special place.

The growth in the number, complexity, and interdependence of risks necessitates the development of integrated risk management models based on AI as a technological platform for identifying threats, forecasting possible consequences, and forming optimal management decisions. The relevance of this issue is confirmed by numerous studies by both domestic and foreign authors regarding digitalization, the integration of innovative technologies, and the application of AI in risk management. At the same time, questions regarding the development of systemic models that would allow not only for the detection and forecasting of risks but also for the transformation of potential threats into new opportunities for ensuring enterprise competitiveness remain relevant.

The aim of the research is the development of theoretical and methodological foundations and practical recommendations regarding the integration of artificial intelligence technologies into the risk management system of enterprises to increase their competitiveness under conditions of digital transformation.

The integration of AI systems into risk management practice allows for increasing the validity of management decisions, ensuring the rapid identification of threats, and forming adaptive management decisions. A conceptual model for the implementation of artificial intelligence in enterprise risk management is proposed, which includes the following stages:

• Risk identification using data mining.
• Risk assessment utilizing machine learning algorithms and neural networks.
• Forecasting scenarios of event development using intelligent expert systems.
• Formulation of recommendations regarding management decisions.
• Real-time monitoring and adjustment of risk management systems.

The main advantages of such an approach are determined: increased information processing speed, growth in the objectivity and accuracy of forecasts, reduction of the human factor influence, and the possibility of automated adaptation to dynamic changes in the external environment.

AI systems, due to their ability for deep analysis of heterogeneous data and finding hidden patterns, allow not only for the timely detection of potential risks but also for the assessment of the degree of their impact on the financial and economic performance indicators of the enterprise. The application of AI provides additional competitive advantages through the possibility of strategic planning based on objective forecasts, identifying new business opportunities, and reducing operating costs.

Practical recommendations include the formation of a unified information ecosystem, the definition of priority areas for AI application, the selection of a technological platform and toolkit, and personnel training.

The conclusions confirm the feasibility of integrating AI into the enterprise risk management system as an effective tool for minimizing threats and ensuring stable development in the digital economy. The proposed model allows for the creation of an adaptive, multi-level risk management system, which, in turn, ensures the growth of enterprise competitiveness in national and global markets.