Model of formation of enterprise performance under the conditions of artificial intelligence systems implementation

Abstract

Methods. The methodological basis of the study is formed by scientific works of domestic and foreign scholars in the field of digital transformation of enterprises, statistical materials of the National Bank of Ukraine, and analytical reports of consulting companies and industry studies on artificial intelligence implementation. The study's results were obtained through methods of analysis and synthesis – used to generalize the economic prerequisites for implementing artificial intelligence systems at enterprises and to identify the relationships between external constraints on business operations and adaptive management decisions; logical generalization and abstraction – for constructing a conceptual model of enterprise performance formation under conditions of artificial intelligence implementation; comparative analysis – for comparing data from industry studies on the effectiveness of artificial intelligence implementation in enterprise activities; a systemic approach – for the comprehensive generalization of economic prerequisites, benefits, and classification of risks associated with artificial intelligence implementation at the enterprise level. Results. The article summarizes the economic prerequisites for implementing artificial intelligence systems at enterprises under conditions of digital transformation and the influence of wartime macroeconomic constraints. The dynamics of business expectations and sectoral indices of industry and construction, based on National Bank of Ukraine data, are analyzed, revealing the impact of energy resource shortages, rising production costs, and a lack of qualified personnel on enterprises' management decisions regarding the implementation of intelligent technologies. A conceptual model of enterprise performance formation is proposed, reflecting the sequence of external constraints, operational consequences, adaptive mechanisms, and management tools. The economic benefits of artificial intelligence implementation are systematized at the operational, tactical, and strategic levels of management. The risks of implementing artificial intelligence in enterprise business processes are classified into five groups. Novelty. A conceptual model of enterprise performance formation under conditions of artificial intelligence systems implementation is proposed, which, unlike existing approaches, reflects the cause-and-effect relationship between external macroeconomic constraints and the choice of specific business process automation tools. Practical value. The study's results have an applied nature, as they contribute to forming a well-grounded approach to management decision-making regarding the feasibility of implementing artificial intelligence systems at enterprises, considering the full range of expected economic benefits and associated risks.