Advancements in computing, data availability, and artificial intelligence/machine learning (AI/ML) technologies have revolutionized operational efficiency and predictive maintenance. Water utilities can capitalize on these developments to enhance operations and maintenance. By integrating weakly supervised learning into ML Operations, utilities can overcome challenges like limited labeled data and high costs associated with data annotation. The adoption of agile methodologies and collaborative team structures can significantly improve the development, deployment, and maintenance of models, ensuring that water utilities are well-equipped to meet future challenges with AI/ML solutions.