Use of artificial intelligence for optimizing business operations in crisis conditions of war

Abstract

The studyʼs relevance is due to the need to develop practical enterprise management tools where traditional management models lose their effectiveness due to failures in logistics chains, resource shortages, and increased cyber risks. The study aims to analyze the possibilities of using artificial intelligence (AI) to optimize business operations in crisis conditions of war, emphasizing adapting to limited resources, minimizing risks, and ensuring the continuity of the enterprise's operational activities. Methods. The research methodology is based on systems analysis to assess the impact of intelligent systems on enterprises' management processes in wartime conditions. Comparison and generalization methods are used to evaluate the effectiveness of AI in various management areas. Results. It was established that implementing AI tools contributes to increasing the efficiency of management processes by automating resource monitoring, adapting logistics routes, and integrating risk management systems. It was found that using machine learning algorithms allows for the timely adjustment of operational plans to changes in external conditions, particularly in logistics and inventory management. It was proven that demand forecasting and resource allocation automation systems increase planning accuracy and reduce the risks of losses in crisis war conditions. The studyʼs scientific novelty lies in its development of recommendations for integrating AI into strategic business management processes, emphasizing adapting business models to war conditions. Conclusions. It is proven that using AI allows for the formation of adaptive resource management strategies and the adjustment of operational processes in conditions of instability and disruption of logistics chains. It was found that the main problems of integrating innovative digital technologies remain high cyber risks, a lack of qualified personnel, and limited access to data due to disruption of the communication infrastructure. Prospects for further research include developing models to assess the effectiveness of implementing AI systems to automate management processes in crisis conditions.