Managerial decision support system using an integrated model of AI and big data analytics

Artificial intelligence (AI) has progressed to the point that it is now integrated into real-world decision support systems and significantly impacts decision-making in management. It is used in a range of areas, including computer science and information technology. This research presents the Integrated Multi-Criteria Decision-Making Model (IMCDMM). Deep algorithms are used to make multi-criteria derivations. This paper focuses on a subset of the components that come together to form an integrated decision-making model that incorporates big data, business intelligence, and decision support systems for organizational learning to deliver the decision-maker with a consistent visualization of decision-related opportunities. The proposed research can provide a comprehensive literature analysis demonstrating how deep learning algorithms and multi-criteria decision-making techniques can be applied to handle significant managerial data problems. Besides, this study discovers by merging multiple criteria with deep learning technologies to construct a decision-support system for big data processing. The proposed IMCDMM framework achieve an acceptability ratio of 92.4%, a performance ratio of 94.5%, an efficiency ratio of 95.5%, a satisfactory user level of 91.8%, a prediction ratio of 93.7%, a decision-making level of 91.5%, and the precision ratio of 92.5% when compared to other methods.