Intelligent Decision Support Systems in Management Information Systems Using Hybrid AI Models

Abstract

This study offers the framework of an Intelligent Decision Support System (IDSS) that leverages Hybrid Artificial Intelligence (AI) models consisting of rule-based, machine learning, and deep learning components for Management Information Systems (MIS). The system is designed to improve decision making in terms of accuracy, responsiveness, and adaptability through a direct interface to the enterprise MIS that processes real-time data for context sensitive feedback. An outcome based assessment approach was used to measure the performance of the hybrid IDSS across various business scenarios, and results showed improvements of 22% in decision accuracy, 30% in response time latency, and 25% in perceived system reliability over traditional Decision Support Systems (DSS) and standalone AI models. The study also offers a practical hybrid AI solutions adoption readiness matrix and a cost-benefit analysis to assist organizations in adopting these technologies towards making intelligent, real-time decisions within the robust frameworks of modern, intelligent Management Information Systems.