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@article{195180,
        author = {Mr R Rangaraj and Ms. Jeyasri J and Ms. LK Sujibala},
        title = {AI-Driven Business Intelligence Systems for Predictive Decision Making},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {7616-7618},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195180},
        abstract = {In today’s data-driven business environment, organizations increasingly rely on Business Intelligence (BI) systems to support strategic and operational decision-making. Traditional BI platforms mainly focus on descriptive and diagnostic analytics, which limits their ability to uncover hidden patterns and generate deeper insights from large volumes of data. To address this limitation, this study proposes an AI-driven Business Intelligence framework that integrates unsupervised learning techniques into conventional BI architecture to enhance predictive and analytical decision-making. The proposed framework utilizes historical sales and customer behavioral data stored in cloud-based data warehouses. Unsupervised learning techniques such as clustering and association analysis are applied to discover hidden patterns, customer segments, and relationships within the data without relying on labeled datasets. These insights help organizations better understand customer behavior, identify emerging market trends, and support intelligent business strategies.
Furthermore, the framework leverages cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud to enable real-time data processing and scalable analytics. Real-time dashboards and visualization tools provide decision-makers with interactive insights, allowing them to monitor key performance indicators and respond quickly to changing business conditions. By combining artificial intelligence techniques with cloud-based business intelligence infrastructure, the proposed system aims to improve data-driven decision-making and enhance overall business performance.},
        keywords = {Business Intelligence (BI), Artificial Intelligence (AI) predictive Analytics, Machine Learning Decision Support systems Sales Forecasting.},
        month = {March},
        }