Publication Details
Abstract
The integration of artificial intelligence (AI) into Management Information Systems (MIS) and Business Analytics is reshaping the way organizations manage operations, make decisions, and sustain competitive advantage in dynamic markets. AI-enabled MIS transforms traditional reporting systems into intelligent platforms that learn from data, anticipate trends, and provide actionable insights. In logistics and supply chain management, AI optimizes inventory management, demand forecasting, route planning, and supplier coordination, thereby reducing delays, lowering operational costs, and enhancing customer satisfaction. Beyond operational efficiency, AI-driven systems support proactive risk management by detecting anomalies, forecasting potential disruptions, and enabling timely interventions, thereby increasing organizational resilience. AI also plays a critical role in human resource development by identifying skills gaps, providing personalized training, and fostering continuous learning. However, organizational readiness, data quality, and employee digital literacy remain key challenges to effective AI adoption. Ethical and regulatory considerations, including data privacy, algorithmic bias, and transparency, further complicate implementation and necessitate robust governance frameworks. Case studies in healthcare and business illustrate AI’s potential to improve decision-making, reduce errors, and enhance productivity, provided systems are strategically aligned with organizational goals and supported by skilled personnel. Emerging trends, including generative AI and the democratization of AI, indicate a shift toward broader accessibility, continuous innovation, and integration into strategic planning. This study highlights that AI-enabled MIS is not merely a technological upgrade but a strategic enabler that enhances efficiency, drives innovation, strengthens resilience, and creates sustainable value.