Water resource management is an urgent problem with climate change, urbanization, and rising demand. The conventional water management techniques are generally inefficient, non-real-time adaptable, and lacking in predictive capabilities. This article suggests an AI-based Smart Water Resource Management System utilizing machine learning, IoT sensors, and real-time data analysis to maximize water distribution, track quality, and forecast demand trends. By combining predictive analytics and anomaly detection AI models, the system supports better decision-making for sustainable water management. The suggested framework not only promotes efficient use of water but also supports reducing wastage and dealing with water scarcity challenges. The research proves the applicability of AI-based techniques in real-time monitoring of water, resource distribution, and sustainability using experimental findings and case studies.