Old Pipes, New Tricks: AI Takes the Night Shift

Forrester finds AI-driven predictive maintenance slashed unplanned downtime 34% at water utilities, marking a shift to everyday operations.

1 Jul 2026

Forrester Research found that artificial intelligence-driven predictive maintenance reduced unplanned downtime by 34 percent at water utilities in 2026, a shift analysts described as moving the technology from experimental use into standard infrastructure. Paired with internet-connected water management systems, the tools are changing how utilities manage costs, meet regulatory standards and safeguard public health. That transition, researchers said, has outpaced earlier expectations.

Utilities reported financial gains from energy savings and more precise chemical dosing, according to the findings. Compliance violations declined as well, easing both regulatory exposure and administrative demands on managers. An unexpected benefit has emerged alongside these efficiencies: the systems are capturing operational knowledge from veteran staff before retirement, embedding decades of field expertise into automated processes.

A.J. Martins, chair of digital infrastructure in utilities, framed the public health implications directly. The combination of sensors and machine learning, Martins said, reduces overhead while enabling earlier detection of contamination, a capability once limited to the largest, best-resourced utilities.

Yet the technology's reach appears to be widening rather than staying concentrated among major operators. Forrester's data suggests predictive models grow more accurate as sensor networks accumulate operational history, with utilities that adopted the systems earliest now seeing compounding returns. Smaller utilities, previously unable to afford advanced monitoring, are gaining access through more affordable, scalable platforms, according to the report.

Some caution is warranted in interpreting the pace of adoption, since the findings reflect early data from a technology still being integrated across a fragmented industry with varying infrastructure and funding levels. Still, the direction is clear enough that regulators and utility operators are treating it as a meaningful trend rather than a passing pilot program.

For an industry contending with aging pipe networks and mounting climate pressures, the timing carries weight. Reliable, predictive water management has become less a competitive advantage than a baseline expectation, analysts suggested. The results could shape infrastructure policy and utility investment in the years ahead.