AI Steps Into Wrocław’s Aging Water Pipes

MPWiK Wrocław deploys AI with Deloitte and AWS to predict pipe failures and push utilities toward smarter, data-driven planning

13 Feb 2026

Europe’s ageing water networks are coming under strain, prompting utilities to seek new ways to prevent costly breakdowns. In Wrocław, Poland, the municipal water company MPWiK has introduced an artificial intelligence platform designed to predict pipe failures before they disrupt roads and households.

Developed with Deloitte and run on Amazon Web Services’ cloud infrastructure, the system marks a shift from reactive repairs to preventive maintenance. Rather than responding to bursts after they occur, engineers are able to identify sections of the network that carry the highest risk of failure and intervene earlier.

The software analyses hundreds of variables, including pipe age, construction materials, soil conditions, pressure levels and historical repair records. The aim is to convert years of operational data into practical guidance for daily decisions. According to project leaders, the model feeds directly into management workflows, allowing investment to be prioritised on measurable risk rather than judgement alone.

The need for change is pressing. Much of Europe’s water infrastructure was built decades ago. Failures can force street closures, interrupt supplies and place unexpected pressure on municipal budgets. Emergency repairs are often more expensive and disruptive than planned upgrades.

Cloud computing underpins the Wrocław initiative. The platform processes large volumes of data and updates its forecasts as new information becomes available. Changes in weather patterns or water usage can therefore be incorporated into risk assessments, giving managers a more current view of network vulnerabilities.

The project reflects a broader trend among public utilities, which are increasingly working with global consultancies and technology providers to modernise essential services. Digital tools once associated with finance or retail are being applied to physical infrastructure.

There are limits. Predictive systems depend on reliable data, secure networks and close oversight. Poor data quality can weaken even advanced models, while cyber risks remain a concern for operators of critical infrastructure.

Even so, the Wrocław programme illustrates how municipalities are seeking to extend the life of ageing assets while managing tighter budgets. Whether such systems can be scaled across Europe’s fragmented water sector remains an open question.