Artificial intelligence has significantly enhanced Decision Support Systems (DSS) by enabling organizations to process growing volumes of complex data and make more informed, timely decisions. As data environments become increasingly dynamic, there is a greater need for intelligent, adaptive, and explainable decision-support capabilities. The evolution of AI in DSS has progressed from foundational models such as Selfridge’s Pandemonium, which introduced hierarchical pattern recognition concepts, to more advanced methodologies capable of analyzing complex relationships, behaviors, and events. Over time, different AI approaches have evolved and converged, leading to modern platforms that combine human expertise, automation, machine learning, and explainable analytics. These advancements allo

Join for free to read