In the present study a novel conceptual framework for an intelligent decision support system (IDSS) is proposed, specifically designed with consideration of the unique operational requirements of small enterprises. The primary objectives of the research are twofold: first, to conduct an in-depth analysis and critical evaluation of existing theoretical approaches to decision support in the small and medium-sized enterprise segment; second, to develop a specialized IDSS model tailored to advisory services for this class of organizations. The methodological foundation of the research consisted of a scrupulous systematic review of scientific publications from the last 5 years devoted to the implementation of artificial intelligence methods in the management processes of small and medium-sized enterprises, as well as to the key directions of development in explainable AI (XAI). As a result, the principal architectural design principles and technological components ensuring the effective functioning of such systems were identified. In conclusion, illustrative case studies of the application of the developed IDSS in tasks of strategic market positioning and financial diagnostics of small businesses are presented. These examples may serve as practical guidelines for IT solution developers, consulting firms, and academic researchers oriented toward the digital transformation of small and medium-sized enterprises.

intelligent decision-support system, small business, business consulting, artificial intelligence, machine learning, explainable AI, hybrid models, decision-making, digitalisation, conceptual model.

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