<p>Innovative, sustainable solutions are necessary to address the issue of water scarcity. Water scarcity and wastage are escalating issues resulting from inefficient irrigation, pollution, inadequate leak detection, climate change impacts, and urban water mismanagement. Effective water management and conservation necessitate the implementation of advanced technology, as conventional methods are insufficient to address these challenges. This research aimed to address a deficiency in our comprehension of how artificial intelligence (AI) and machine learning (ML) may promote water conservation across many industries. Research on enhancing smart grids and leak detection for urban water management, optimizing agricultural irrigation, and minimizing industrial water use through predictive maintenance and process optimization is scarce. To effectively manage resources, intelligent technologies provide predictive analytics that enable accurate forecasting of water demand and availability. Smart irrigation systems utilize real-time data, such as soil moisture and weather forecasts, to optimize watering schedules through artificial intelligence and machine learning. Simultaneously, identifying and controlling leaks is advantageous for urban systems. Moreover, these systems deliver real-time data, ensuring safe water utilization and assessing user behavior to promote water conservation. Advancements in smart technology should enhance the efficacy of water conservation efforts. This work contributes to the current literature by endorsing integrated research, emphasizing the need of scalable and adaptable AI and ML solutions, and delineating their capacity to transform water management methods. The authors advocate for further collaboration between academics and practitioners to explore methods for utilizing AI and ML to enhance sustainable water usage. This study’s findings will benefit Internet of Things (IoT) and AI research focused on enhancing profitability and quality standards in the water business.</p>