Objective: This paper focuses on ways artificial intelligence and business intelligence technologies can be utilized to improve the efficiency of an organization, this paper aims to propose a framework for organizational use to leverage AI and its performance in organizations. Theoretical Framework: In this topic, the author proposes a framework for integrating AI and BI, which includes the following components: data collection and statistical analysis, machine learning algorithms, visualization, and integration with BI systems. Method: This study will employ a statistical methodology called multiple regression, the analysis helps to examine the relationship between a dependent variable (organizational performance) and multiple independent variables (extent of BI integration, extent of AI integration, and AI and BI integration). Results and Discussion: Combining AI and BI in business processes improves decision-making, increases efficiency, and enhances customer experiences. AI automates complex processes, detects patterns, and predicts based on vast data, enhancing BI systems. AI-powered BI systems give businesses a competitive edge by improving decision-making, performance, and customer engagement. Integrating AI and BI leads to improved organizational performance. Research Implications: This paper stresses the significance of evaluating organizational structure before implementing AI-based systems. It guides infrastructure requirements for successful AI implementation in business, emphasizing security implications when making decisions based on AI-generated data. Originality/Value: Integrating AI and BI can lead to faster and more efficient business processes, resulting in higher performance. AI technology can revolutionize decision-making across industries, including business. Practical recommendations are available on how to use AI to improve decision-making in organizations.