AI-Powered Business Intelligence and Decision Making:

This research paper, titled “AI-Powered Business Intelligence and Decision Making: A Literature Review and Conceptual Framework,” explores the integration of Artificial Intelligence (AI) and Business Intelligence (BI) to support effective, data-driven business decision-making. The paper reviews existing literature on machine learning, predictive analytics, explainable AI, and decision support systems. It proposes an eight-stage conceptual framework covering business problem identification, data collection, data validation, data integration, analytics, explanation of results, human decision-making, and continuous monitoring. The study also highlights challenges related to data quality, privacy, security, algorithmic bias, transparency, and model maintenance. A retail inventory example illustrates how AI-based forecasting can support managers in making informed decisions. This work is a literature review and conceptual study. The proposed framework has not yet been implemented or experimentally validated. Future work may involve developing a prototype and evaluating its effectiveness in a real-world business environment.