How AI Leak Detection Is Rewriting Water Utility Work

AI-powered leak detection is moving into the field, helping water utilities cut losses, speed repairs, and meet rising performance demands

2 Feb 2026

The change is happening underground. Beneath city streets and inside utility vans, artificial intelligence is altering how water leaks are found and fixed. It is not flashy. But it is beginning to matter.

For decades, leak detection was a slow, reactive business. Crews chased alarms after water had already been lost. Data were sent back to headquarters for analysis, often days later. With pipes ageing and workforces stretched thin, much effort went into confirming problems that sometimes turned out not to exist.

That balance is now tilting. A growing number of utilities are deploying AI tools that deliver insight directly to field crews, in real time. Instead of waiting for instructions, workers can identify and verify leaks on site. Repairs that once took weeks can be planned and completed in days.

Firms such as FIDO Tech exemplify the shift. Their systems are built to work even when connectivity is weak or absent, a common condition underground or in remote areas. The emphasis is not on adding more dashboards, but on helping crews make quicker decisions where the leak actually is.

Analysts see this as part of a broader rethink in digital water strategy. The old measure of success, how much data could be collected, matters less than how easily that data can be used during a busy shift. Tools that reduce friction and give crews confidence in the field are gaining favour.

The pressure on utilities is mounting. In America some lose more than 10% of treated water before it reaches customers. Regulators and ratepayers, meanwhile, want clearer reporting and visible reductions in non-revenue water. In that setting, AI-driven detection looks less like a technology upgrade and more like an operational necessity.

Big suppliers are taking note. Companies such as Xylem and EPIC iO are also blending sensors, analytics and workflows into systems designed for frontline use rather than central offices alone.

Adoption is not painless. Training takes time. New tools must fit with existing systems. Faster detection can overwhelm repair crews if priorities are poorly set. Technology does not remove the need for planning.

Even so, many utility leaders judge the trade-off worthwhile. As AI tools become cheaper and easier to use, smarter leak detection is moving from experiment to expectation. Quietly, and below ground, it is becoming central to the future management of water.