AI-Augmented Business Intelligence Framework for Predictive and Prescriptive Analytics

Abstract: The integration of Artificial Intelligence (AI) into Business Intelligence (BI) systems represents a strategic transformation in how businesses interpret data and execute decisions. While traditional BI reports are often static and limiting their ability to solve complex business problems, this paper proposes an AI-Augmented Business Intelligence framework designed to bridge the "decision gap" through predictive and prescriptive analytics. By leveraging ERP data via OData APIs and integrating Machine Learning, Natural Language Processing (NLP), and Agentic AI, the framework delivers real-time insights that improve forecasting accuracy by 15–20%. We examine the advantages of this synergy, including increased operational efficiency, personalized customer experiences, and the role of key tools like Tableau, Power BI, and IBM Watson in enhancing data visualization. the findings indicate that the future of BI is inextricably coupled with AI advancements, enabling organizations to achieve long-term growth and a competitive edge in an increasingly data-driven world.

Keywords: Business Intelligence (BI), Artificial Intelligence (AI), Predictive Analytics, Data-Driven Decision Making, Real-Time Insights