| Annotation: | Methods. The research methodology is based on methods of theoretical generalization and systematization of scientific literature, comparative analysis of contemporary decision-making concepts, content analysis of publications issued by international analytical organizations and consulting companies, and logical synthesis aimed at developing practical recommendations for improving managerial effectiveness. Particular attention is devoted to the interaction between rational analysis, psychological factors, organizational resilience, and artificial intelligence technologies in the decision-making process. Results. Interdisciplinary approaches to managerial decision-making that integrate quantitative, behavioral, and digital management support methods have been systematized. The study identifies the distinctive role of artificial intelligence and digital decision support platforms in transforming contemporary managerial processes. It substantiates the importance of human capital, behavioral factors, and organizational resilience in enhancing the effectiveness of managerial decision-making under conditions of uncertainty. .Novelty. The scientific novelty of the study lies in the improvement of an interdisciplinary model of managerial decision-making that combines rational-analytical, behavioral-psychological, and technological dimensions within a unified conceptual framework. The research advances the understanding of artificial intelligence not as an autonomous automation tool but as an organizational capability that emerges through the interaction of digital technologies, human capital, and corporate governance mechanisms. This approach broadens existing perspectives on the role of AI in management and highlights the importance of maintaining human responsibility and strategic judgment in technology-supported decision processes. Practical value. The practical significance of the findings lies in their applicability for enterprise managers seeking to improve decision quality under conditions of high uncertainty. The proposed recommendations can be used to implement scenario planning practices, to develop AIbased decision support systems, to strengthen organizational resilience, and to enhance managerial competencies related to risk management, cognitive bias mitigation, and digital business transformation. |
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