Enhancing Data-Driven Decision-Making: The Role of Decision Tree Algorithm at the Intersection of AI and Business Intelligence

Abstract

The convergence of Artificial Intelligence (AI) and Business Intelligence (BI) has revolutionized data-driven decision-making across various industries. This paper explores the intersection of AI and BI, delving into their applications, implications for decision-making, and synergistic potentials. Employing decision tree methodologies, the study systematically investigates the intricate interplay between AI, BI, and data-driven decision processes. By analyzing real-world data and employing decision tree models, the research uncovers significant patterns, trends, and decision pathways that characterize the integration of AI and BI in organizational settings. Through a comprehensive review and synthesis of existing literature, the study identifies challenges, opportunities, and future directions in leveraging AI-driven BI solutions to enhance decision-making effectiveness. These findings provide valuable insights for businesses, policymakers, and researchers, informing strategic investments and fostering innovation in the age of data-driven decision-making.