AI Agent Operational Lift for Clayton County Water Authority in Morrow, Georgia

Why AI matters at this scale

Clayton County Water Authority (CCWA) is a mid-sized public utility serving Morrow, Georgia, and surrounding communities since 1955. With 201–500 employees, it operates water treatment plants, distribution networks, and wastewater facilities—critical infrastructure that must balance aging assets, regulatory compliance, and growing demand. At this scale, AI offers a pragmatic path to do more with existing resources, avoiding the cost and complexity of large-enterprise overhauls while still capturing significant efficiency gains.

What CCWA does

CCWA provides drinking water, wastewater treatment, and stormwater management to a diverse customer base. Its operations span source water intake, treatment, pumping, storage, and thousands of miles of pipes. Like many water authorities, it faces challenges such as non-revenue water (leaks), energy-intensive pumping, and stringent water quality standards. The workforce includes operators, engineers, field crews, and administrative staff—a size that allows targeted AI pilots without overwhelming change management.

Why AI now

Utilities of this size often have digitized core processes (SCADA, GIS, billing) but lag in advanced analytics. AI can unlock value from data already collected—flow meters, pressure sensors, water quality monitors, and customer usage. With cloud costs falling and pre-built AI solutions for water emerging, the barrier to entry is lower than ever. Moreover, federal infrastructure funding and state revolving funds increasingly favor technology-driven efficiency projects, making now an opportune moment to invest.

Three concrete AI opportunities with ROI

1. Predictive maintenance for pumps and pipes. By training machine learning models on vibration, temperature, and runtime data, CCWA can forecast failures days or weeks ahead. This shifts maintenance from reactive to planned, reducing overtime, emergency part costs, and service disruptions. ROI: A 20% reduction in maintenance spend could save hundreds of thousands annually, with payback within a year.

2. AI-powered leak detection. Using acoustic sensors and flow balance analytics, AI can pinpoint leaks in near real-time. For a system losing 15% of its water, cutting that in half could recover millions of gallons and associated treatment costs. ROI: Water savings alone often justify the investment, plus avoided pipe failures and regulatory penalties.

3. Water quality anomaly detection. Continuous monitoring with AI can detect subtle changes in turbidity, chlorine residual, or pH that precede contamination events. Early alerts enable faster response, protecting public health and avoiding boil-water advisories. ROI: Avoided crisis management costs and reputational damage, plus streamlined compliance reporting.

Deployment risks for this size band

Mid-sized utilities must navigate limited IT staff, potential resistance from veteran operators, and the need to integrate AI with legacy OT systems. Data quality and silos are common hurdles. A phased approach—starting with a single high-impact use case, using vendor-hosted solutions, and involving frontline staff in model validation—mitigates these risks. Cybersecurity must be addressed upfront, especially when bridging IT and OT networks. With careful planning, CCWA can become a model for AI adoption among regional water authorities.