Abstract
AI-powered Decision Support Systems (AI-DSS) enhance analytical capabilities through advanced data processing, predictive analytics, and intelligent decision support. This study investigates the impact of AI-powered DSS on decision-making effectiveness across multiple sectors. A quantitative research design was employed using a structured questionnaire distributed to 33 professionals and decision-makers experienced in AI-based DSS. Decision-making effectiveness was assessed through decision accuracy, decision-making speed, operational efficiency, and user satisfaction. Data were analyzed using descriptive statistics, Pearson correlation, and simple linear regression. The results show a moderate positive correlation between AI usage and decision-making effectiveness (r = 0.550, p < 0.001). Regression analysis further demonstrates that AI utilization significantly predicts decision-making effectiveness (B = 0.265, t = 3.664, p < 0.001). These findings indicate that greater utilization of AI-powered DSS is associated with improved decision outcomes, particularly in decision accuracy, response speed, and operational efficiency. The study also demonstrates the applicability of AI techniques, including machine learning, neural networks, fuzzy logic, and Bayesian modelling, across diverse industrial contexts. Overall, the findings provide empirical evidence that AI-powered DSS contribute significantly to organizational decision-making effectiveness across multiple sectors.