GenAI models for urban water systems: Opportunities, challenges and future directions

Abstract Generative artificial intelligence (AI), particularly large language models, offers transformative potential for the management and operation of urban water systems. As water utilities face increasing pressures from climate change, ageing infrastructure and population growth, AI-driven tools provide new opportunities for real-time monitoring, predictive maintenance and enhanced decision support. This article explores how generative AI can revolutionise the water industry by enabling more efficient operations, improved customer engagement and advanced training mechanisms. It examines current applications, such as AI-integrated supervisory control and data acquisition systems and conversational interfaces, and evaluates their performance through emerging case studies. While highlighting the benefits, the article also addresses key challenges, including data privacy, model reliability, ethical considerations and regulatory uncertainty. Through a balanced analysis of opportunities and risks, this study outlines future directions for research and policy, offering practical recommendations for the responsible adoption of generative AI in urban water management to improve resilience, efficiency and sustainability across the sector.