Purpose of the study – to analyze intelligent approaches to the formation of optimal managerial decisions in decision support systems (DSS) and to assess their practical significance under conditions of uncertainty and resource constraints. The tasks of the work include a review of modern intelligent methods used in DSS, an examination of their role in enhancing the soundness of managerial decisions, as well as an investigation of the conditions for the successful implementation of such systems. The methodological basis consisted of systematic and comparative analysis, synthesis of scientific literature, and analysis of practical case studies on the implementation of intelligent approaches in management processes. The results of the study showed that the intellectualization of DSS improves the quality of managerial decisions through multi-criteria evaluation, dynamic modeling, and the integration of artificial intelligence methods; however, its effectiveness depends on the transparency of recommendations and the system's adaptability to changing conditions. The practical significance of the work lies in identifying the key components for the successful implementation of intelligent DSS, including the formation of an input data pipeline, development of a computational core, ensuring interpretability of results, and implementing mechanisms for iterative decision updates.