Evolve 2026/ Session notes

Flowing Forward: AI and the Future of Water

EVOLVE 2026 · MIAMI · TRACK SESSION · SESSION 07

Shaun Dipnall, Chief Delivery Officer, Sand (moderator) · Commissioner Tommy Calvert, Bexar County · Calvin Farr · Mitch Dabling · Fredrick Royan, Frost & Sullivan · 6 min read

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THE 60-SECOND READ

Water is the utility nobody thinks about until it fails, and much of the infrastructure carrying it in the US is 60 to 70 years old. The panel’s shift in one line: stop reacting to the loudest problem in the system and start prioritizing by consequence. Use the data to decide what to fix now, what to defer, and what failure would actually cost.

Key Highlights

By the numbers (data points sidebar)

60-70 yrs
age of much US water infrastructure
5 → 2
workers replaced for every five who leave
Bexar County residents today
0 M
more expected within a decade
+ 0 M

In their words

“Utilities are built by families. There are folks with institutional knowledge that isn’t documented anywhere. And they retire.”
Calvin Farr, CEO, Prince William Water

Notes

Asked to rate themselves on the keynote’s dark-noisy-intelligent scale, the panel was honest: ‘good noisy’ at best. The data exists. It just isn’t being used. Dashboards get built and then drift to the wayside when nobody trusts them. The fix offered was cultural: bring veteran operators into the dashboards, document what’s in their heads, and let their feedback train the models.

Politics got its own warning. Policy is not data-driven, one commissioner reminded the room. AI products will face opposition over data-center energy and water use, whatever their merits. So utilities and vendors need community engagement and an energy-saving story as much as they need algorithms. Cooperative purchasing agreements can move good products through procurement faster.

Two small consumer stories made the feedback point best. A smart meter flagged a leak, and nobody ever asked the customer whether it was right. Another alert went to the wrong address entirely. Models that never learn whether they were correct stay wrong.

From the room (session gallery)

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Physical AI for Critical Infrastructure.