Drinking water production and distribution is critical to public health, socioeconomic growth, and urban development . Water demand prediction is a critical component in drinking water production. Traditional methods for estimating water demand often lead to either overestimation, resulting in high costs and waste of resources, or underestimation, resulting in water supply shortages during peak times . Additionally, water systems suffer from losses because of leaks and inefficiencies with severe financial and operational consequences . ML models are a compelling solution to predict drinking water production and demand and identify system losses with greater precision than conventional approaches. This section examines how ML contributes to the management of water resources, the prediction of water demand, and the assurance of sustainability and reliability in drinking water supply systems (Table ).