Abstract : Artificial Intelligence (AI) has emerged as a transformative technology that significantly enhances the capabilities of Decision Support Systems (DSS). Traditional decision support systems primarily relied on structured databases, statistical models, and rule-based algorithms to assist managers in decision-making processes. However, the increasing complexity of business environments and the rapid growth of big data have created the need for more intelligent and adaptive decision-making tools. Artificial intelligence technologies such as machine learning, neural networks, natural language processing, and expert systems enable decision support systems to analyze large volumes of data, recognize patterns, and generate predictive insights. Intelligent Decision Support Systems (IDSS) combine the analytical power of AI with traditional DSS frameworks to improve decision accuracy and efficiency. These systems can assist decision-makers in various domains including healthcare, finance, business management, and strategic planning. AI-based decision support systems can process both structured and unstructured data, enabling organizations to derive meaningful insights from diverse information sources. Research has shown that AI-driven DSS significantly improve decision-making speed, reduce uncertainty, and enhance organizational performance (Power, 2014; Turban et al., 2019). This theoretical study examines the role of artificial intelligence in enhancing intelligent decision support systems by reviewing existing literature and analyzing key developments in this field. The study highlights the benefits, challenges, and future potential of AI-enabled decision support systems in modern organizations.
Keywords : Artificial Intelligence, Decision Support Systems, Intelligent Systems, Machine Learning, Data Analytics, Business Intelligence, Intelligent Decision Making.
Cite : Singh, P. P. (2026). Role of Artificial Intelligence in Intelligent Decision Support Systems (1st ed., pp. 167-172). Noble Science Press. https://noblesciencepress.org/chapter/nspebgtrdbaip2026ch-18
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