Abstract: The runaway path of global urbanization combined with unstable climate change has subjected municipal water infrastructure to record stress. Conventional reactive water management frameworks based on static regulations are inherently unsuitable for providing the required levels of efficiency and robustness to contemporary urban settings. One of the prime symptoms of this systemic failure is the existence of Non-Revenue Water (NRW), which undetermined the commercial feasibility of utilities and environmental abundance of portable water. Predictive flow control through Artificial Intelligence (AI) is a required technology transformation, redefining the fundamental operations of utility companies from passive monitoring to self-optimizing systems. This survey lays out the critical role of AI incorporation to enable sustainable urban water management, outlining its technical underpinnings in the Internet of Things (IoT) and Supervisory Control and Data Acquisition (SCADA) systems. The central application, Dynamic Pressure Management (DPM), delivers measurable worth by facilitating the reduction of NRW by large amounts estimated at 0.79 gallons per service connection per day for each PSI decrease and garnering enormous Operational Expenditure (OpEx) savings through optimized pumping.

In addition, AI improves the longevity of infrastructure by preventing pressure transients and extends its applications to crucial flood risk reduction, ensuring overall urban climate resilience. Strategic investment in such a transition requires careful financial planning using models such as Performance-Based Service Contracting (PBSC) and strict governance practices to take on the amplified cybersecurity threats, especially those to data integrity and autonomous control loops. Index Terms-Artificial Intelligence (AI), Dynamic Pressure Management (DPM), Non-Revenue Water (NRW), Internet of Things (IoT), SCADA, Urban Resilience, Cybersecurity.

Keywords: Internet of things (IoT) sensor, Real-time Monitoring, Artificial Intelligence, Smart Metering, Leak Detection, Predictive Maintenance.

Downloads: | DOI: 10.17148/IARJSET.2025.1211036