Water and wastewater treatment facilities are increasingly challenged by complex operations, limited staffing, and the need to maintain regulatory compliance while minimizing costs. Traditional digital tools such as dashboards often rely on lagging indicators and fail to support real-time decision-making, especially for field-level Operations and Maintenance (O&M) staff. In response, Jacobs, in collaboration with Palantir, developed and deployed a suite of predictive, AI-powered digital tools designed specifically to support O&M personnel in their daily workflows. These tools provide actionable, site-specific recommendations for chemical dosing, aeration control, and maintenance scheduling, delivered directly to staff via mobile devices. The approach emphasizes a “human-in-the-loop” philosophy, where operators retain full authority to accept or reject AI-generated suggestions based on real-world conditions. This model builds trust by leveraging each facility’s historical data and best practices, ensuring transparency and relevance in the recommendations. The development process includes early engagement with plant teams, deep data analysis using machine learning, secure one-way data integration, and flexible deployment pacing tailored to each site. Weekly support meetings and minimal training requirements further enhance adoption and effectiveness. To date, over 50 use cases have been successfully implemented across dozens of facilities, with adoption rates ranging from 65–90%. Reported outcomes include 10–30% reductions in chemical and energy usage, improved maintenance planning, and sustained regulatory compliance. Importantly, the tools have fostered deeper engagement among staff, encouraging discussion and continuous optimization of plant operations. This initiative demonstrates that AI can be effectively integrated into water operations from an O&M-centric perspective, enhancing—not replacing—human decision-making. It highlights the importance of trust, transparency, and staff empowerment in driving successful digital transformation in the water sector.