(untitled) (Journal of Academic Research, 2026)
Artificial Intelligence (AI) has become a key enabler of modern Decision Support Systems (DSS), enhancing decision-making processes across healthcare, business, finance, industry, cybersecurity, education, and smart cities. This systematic review synthesizes evidence from 23 studies published between 2023 and 2026 to examine the applications, benefits, challenges, and future directions of AI-driven DSS. The findings reveal that AI technologies, including machine learning, deep learning, expert systems, predictive analytics, and explainable AI, significantly improve decision accuracy, operational efficiency, resource optimization, and predictive capabilities. Healthcare emerged as the most prominent application domain, where AI supports diagnosis, prognosis, treatment planning, and clinical workflow management. Business and financial sectors utilize AI for strategic planning, forecasting, and supply chain optimization, while industrial applications focus on predictive maintenance and risk assessment. Despite these advantages, challenges such as data quality issues, privacy concerns, algorithmic transparency, ethical considerations, and regulatory limitations continue to affect implementation. The review also highlights a growing shift toward Human-Centered AI, emphasizing collaboration between intelligent systems and human experts. Overall, AI demonstrates substantial potential to strengthen DSS performance when supported by transparent algorithms, reliable data infrastructures, and effective governance frameworks.