<![CDATA[Abstract: The development of digital technology in the Industry 4.0 era has driven the transformation of information management towards intelligent decision-making systems. Decision Support Systems (DSS) are important components that help organizations analyze complex data and make optimal decisions. However, increasing data complexity, the integration of intelligent technologies, and the need for multicriteria analysis pose new challenges in the development of such systems. This study aims to systematically examine the development of management information systems in supporting intelligence-based decision-making, with a focus on hybrid models, artificial intelligence-based approaches, and multicriteria decision-making methods. The methods used include a systematic literature review (SLR) following the procedure developed by Kitchenham. This study analyzes the scientific literature on SPK, artificial intelligence, big data analytics, and multicriteria decision-making methods, including AHP, ELECTRE, and fuzzy logic. The results of the study show that integrating artificial intelligence with a multicriteria decision-making method can increase accuracy, flexibility, and the adaptive system's information management capabilities across sectors such as manufacturing, health, and supply chain management. In addition, a hybrid approach that combines data analytics, computational intelligence, and mathematical decision models is more effective in the face of complexity when making modern decisions. Research. This contributes to the development of intelligence based on system information management and provides direction for future research on integrating intelligent technology into decision-making for system support. Keywords: system information management; system supporters decision; artificial intelligence; multicriteria decision making; Industry 4.0; hybrid decision model; big data analytics]]>
