Carollo Engineers and partners release artificial intelligence and machine learning guidebook for potable reuse

WALNUT CREEK, Calif., July 28, 2026 – A first-of-its-kind guidebook dedicated to artificial intelligence (AI) and machine learning (ML) in potable reuse systems is now available to help water utilities evaluate and implement such technologies. Free to download, the AI & Machine Learning Guidebook for Potable Reuse offers practical guidance for deploying and maintaining AI and ML tools that can improve operational efficiency, support decision-making, and enhance treatment performance. While the guidebook focuses on potable reuse applications, many of its underlying principles apply to conventional drinking water and wastewater treatment systems.

The guidebook was developed through a collaboration between Carollo Engineers, Yokogawa, the National Water Research Institute (NWRI), and Baylor University under the U.S. Bureau of Reclamation-funded research project Data-Driven Fault Detection and Process Control for Potable Reuse with Reverse Osmosis and Membrane Bioreactors.

Shaped by input from a Utility Advisory Board and an Independent Expert Panel representing utilities, researchers, and consultants, the guidebook covers the full AI and ML implementation lifecycle, from foundational concepts and data management to model development, pilot testing, cybersecurity, workforce readiness, and long-term maintenance. Real-world applications addressed include process optimization, predictive maintenance, water quality forecasting, digital twins, and fault detection.

“Artificial intelligence and machine learning have the potential to help utilities make better use of the vast amount of operational data generated every day,” said Andy Salveson, vice president at Carollo Engineers and principal investigator for the project. “This guidebook provides a practical path forward for utilities interested in exploring these technologies, from understanding the fundamentals to successfully implementing and maintaining tools that support more informed operational decisions.”

The guidebook emphasizes that successful AI and ML adoption requires more than technical expertise. Strong data management practices, operator engagement, cybersecurity planning, and organizational readiness are all critical to turning AI and ML potential into real-world results. The publication advocates a phased implementation approach that allows utilities to build confidence, validate performance, and minimize risk.

The AI & Machine Learning Guidebook for Potable Reuse is available as a free download for utilities, researchers, regulators, and water professionals looking to understand and apply AI and ML in potable reuse and related water treatment applications.

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Media Contact:
Cameron McWilliam
Senior Public Relations Manager // Carollo
[email protected]