In today's competitive business environment, organizations are increasingly adopting Artificial Intelligence (AI) to enhance the efficiency of their Management Information Systems (MIS). The integration of AI into MIS has the potential to improve operational efficiency, decision-making processes, and customer satisfaction. This study aims to investigate the impact of AI on business performance by exploring its role in automating processes and providing data-driven insights. A systematic literature review (SLR) methodology was employed to analyze a range of studies on AI integration into MIS, focusing on improving business efficiency. The findings indicate that AI significantly reduces data processing time, increases decision-making accuracy, and improves customer satisfaction. Specifically, AI implementation led to a 66% reduction in data processing time, a 29% increase in decision-making accuracy, and a 20% reduction in operational costs. These results highlight AI's ability to optimize business processes and enhance overall productivity. However, the study also identified key challenges, including the need for high-quality data, specialized workforce training, and ethical considerations surrounding data privacy. This research contributes to both theoretical and practical knowledge by providing a comprehensive understanding of AI's role in MIS. It offers strategic recommendations for organizations aiming to leverage AI to drive operational efficiency and maintain competitive advantage. Future research should focus on exploring synergies between AI and emerging technologies such as big data and the Internet of Things (IoT) to further improve business outcomes.
