In many applications, the right combination of data and algorithms can produce marked improvements in efficiency, speed, and oversight.
Chetan Mistry, Strategy and Marketing Manager at Xylem Africa, WSS.
While some, even most water utilities already use digital monitoring and analytics to manage operations, artificial intelligence can build on these capabilities by identifying patterns in large datasets, enabling predictive insights, and supporting more informed decision-making. Recognising this, around 15% of large water utilities around the world are already using artificial intelligence. This is set to reach 30% by 2026, according to the Xylem Water Technology Trends 2025 report. By 2035, it is expected that three-quarters of water utilities will use some form of AI.
With aging infrastructure, climate variability, and rising water demand placing increasing pressure on water systems, utilities are seeking more resilient and adaptive ways to manage operations. Data-driven and AI-enabled tools are emerging as part of this broader digital transformation in the water sector.
Experts have good reason to be optimistic about AI adoption in the sector. Already, digital water management systems are producing excellent results. For example, Yorkshire Water Services in the UK, which uses Xylem Vue digital services, last year reported a reduction in visible leaks by 57% as well as a reduction in annual distribution main repairs by 30%.
Similar digital and AI-driven capabilities are also being used in industrial water and wastewater operations, where predictive monitoring and process optimisation help improve compliance, reliability, and resource efficiency.
Such outcomes show the hidden capacity at every water management site, says Chetan Mistry, Strategy and Marketing Manager at Xylem Africa, WSS.
"Water distribution and treatment sites produce far more data than they use. But that data gets neglected because of capacity. It would take an enormous amount of time to organise and study the data for patterns and insights. Digital and AI systems are solving those problems. Digital systems record and share accurate and reliable data, which AI systems use to produce planning information, automation, and other improvements, fast."
Water management sites utilise smart data and AI services in several ways.
Real-time process adjustment
Water treatment is at its best when the system can maintain consistency. This is a laborious task because water flows keep changing. Intelligent water systems add intelligence that adjusts processes such as reagent dosing and treatment line control in real time. Site operators define specific scenarios that automatically adjust operations ‌using information from external technologies such as water management applications and business intelligence systems.
Predictive demand and optimisation
AI systems predict conditions to manage demand and optimisation. Predictive maintenance systems rely on predictive analytics and AI-driven models, which use performance data and systems such as digital twins to anticipate maintenance conditions for equipment. Similar technologies have expanded to help water managers forecast demand, such as consumption peaks. They can also optimise energy consumption by adjusting operations based on demand.
Advanced metering infrastructure
Smart meters have improved the performance and efficiency of water distribution networks, using digital technologies to gauge consumption and feed reliable data into water planning systems. Advanced metering infrastructure (AMI) is the next step in that journey. AMI performs remote reading and integrates and processes information into AI systems, significantly reducing information intervals towards almost real-time monitoring and feedback.
Decision support systems
Water utilities are using decision support systems (DSS) to inform real-time medium- and long-term planning and management. DSS tools use AI to analyse large datasets and information from different disciplines, including data from hydrological and meteorological stations, expert knowledge, and local inputs. Such analyses can model different situations, from simulating water bodies to predicting usage patterns.
While these and other data-driven improvements seem attractive, utility and infrastructure managers are not always sure where to start. Successful deployment depends on data quality, integration with existing infrastructure, and organisational readiness. Deploying digitisation can become complicated, which is why leading water technology OEMs like Xylem develop and maintain extensive software platforms designed to meet water utility challenges.
"Companies like Xylem invest substantially in developing water management platforms that are secure, simple to deploy, and make sure the data remain with the utility," says Mistry. "They create interactive and customisable dashboards and reports, which authorised staff and contractors can access on-site through smart devices and computers."
The real advantage of using data-driven water management platforms is not just in the new features. It enables utilities to leverage information they already have: "Data that does nothing only takes up space. But data made useful through cloud-based management software opens additional dimensions for planning and predictive actions such as maintenance."
For more information visit: www.xylem.com/en-za/