The Role of Business Intelligence and Artificial Intelligence in Real-Time Decision Making
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The fusion of Business Intelligence (BI) and Artificial Intelligence (AI) has revolutionized decision-making processes across diverse industries, transforming how organizations utilize data to achieve strategic objectives (Chen et al., 2012). By integrating BI, which focuses on data collection, organization, and visualization, with AI’s predictive and prescriptive capabilities, businesses can move beyond traditional analytics to dynamic, real-time decision-making. This article explores the transformative role of BI and AI, emphasizing their applications in business analytics and operational decision frameworks. AI-powered tools, such as machine learning algorithms and natural language processing (NLP), significantly enhance the capabilities of traditional BI systems, enabling organizations to derive actionable insights, streamline operations, and maintain a competitive edge (Davenport & Harris, 2007).
This study delves into key case studies that highlight the practical implementation of AI-driven BI systems in various industries. These include predictive analytics for forecasting market trends, automated customer segmentation through NLP, and prescriptive analytics for optimizing supply chain operations. Furthermore, the article examines emerging technologies, such as explainable AI (XAI) and edge computing, that are shaping the next generation of real-time decision-making systems. The discussion extends to the challenges and opportunities in integrating these technologies, such as ensuring data privacy, addressing skill gaps, and managing implementation costs. Through a comprehensive analysis, this study aims to provide a holistic understanding of the convergence of BI and AI in the modern business landscape (Sharda et al., 2020).
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Copyright (c) 2025 Amejuma Emmanuel Ebule
This work is licensed under a Creative Commons Attribution 4.0 International License.
