Water and wastewater utilities across California are increasingly adopting AI and machine learning (ML) tools to improve efficiency, reduce costs, and address water sustainability challenges; however, adoption remains uneven. A Bluefield Research whitepaper revealed that less than 50% of the water sector is prepared to leverage AI solutions. Larger and smaller utilities are the most digitally advanced, while medium-sized organizations lag behind.1
The June 2025 report cites an expert who predicts that AI adoption in water treatment facilities, which was 10-15% in mid-2025, will likely increase to 25-30% by the end of the year, but will most likely take more than a decade to fully implement. The barriers to adoption are many, but few have been addressed to date.
At this AC26 session, Andrew Goldberg and Dillon McCormick, from Brown and Caldwell, will identify and discuss obstacles to implementing AI, including gaps in staff digital literacy, data infrastructure, quality challenges, and cybersecurity concerns. Then the focus will turn to practical examples of how utilities can apply AI today and to an introduction of a framework for overcoming these barriers.
“We demonstrate how accessible tools–integrated into existing workflows–can deliver quick wins without large upfront investments,” says Goldberg.
During the conference session, case studies will be presented to show how:
This technology is not intended to be an all-in-one solution for every utility problem. However, different levels of effort and risk are involved in various AI implementations, allowing utilities to begin small.
“The ‘silver tsunami’ of retirements and rapid data growth is straining decision-making at water utilities,” McCormick points out. “Through these examples, we show how water and wastewater utilities can bridge adoption gaps and harness Artificial Intelligence/Machine Learning to solve real-world challenges.”
“This technology interfaces well with centralized and well-organized and managed data. Since many utilities are moving towards this new data paradigm, incorporating AI/LLMs can empower them to get the most out of their effort,” Goldberg said.
The authors are both data scientists with the engineering firm of Brown and Caldwell. Goldberg earned a bachelor’s degree from Lafayette College and a master’s degree in environmental planning and management from the Johns Hopkins Whiting School of Engineering. He specializes in addressing water resource challenges through advanced digital technologies.
McCormick received bachelor’s and master’s degrees from Northeastern University and has experience in large language models, machine learning, data analytics, dashboards, and web applications.
AI adoption in water isn’t theoretical — it’s happening now. Learn how utilities are applying advanced tools, overcoming implementation barriers, and preparing for the future at AC26.
Join us April 7–10 in Sacramento.
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