Generative artificial intelligence (GenAI) is emerging as a catalyst capable of transforming asset management, decision-making and customer engagement in the water sector.
The sector is at an unprecedented turning point. The convergence of ageing infrastructure, a changing workforce, increasing regulatory pressure and the growing effects of climate change is forcing utilities to rethink their strategies and operations.
In this context, GenAI is emerging not merely as a digitalisation tool, but as a strategic enabler of smarter asset management, improved operational decision-making and stronger customer relationships, according to the report Water Technology Trends 2026: A Strategic Guide to the Future of Smart Water, recently released by Xylem Vue.
The report highlights GenAI’s ability to generate contextualised content, including summaries, recommendations and simulations, positioning it as a valuable tool for decision-making in complex environments. This marks a significant step beyond advanced analytics and traditional machine learning, which have largely focused on specific applications such as leak detection and demand forecasting.
Global adoption gathering pace
The adoption of GenAI in the water sector is becoming a global trend, with initiatives underway across the US, Europe, Asia-Pacific and the Middle East. While more mature markets currently lead deployment, the report noted that “operational pressure and the need for efficiency are driving digitalisation worldwide”.
Among the highest-impact applications identified are strategic infrastructure planning and performance optimisation. AI-driven conservation platforms can support the early detection of water losses while encouraging more responsible water consumption among customers.
Operational optimisation is another major focus area. GenAI is helping utilities narrow funding gaps in operations and maintenance through task automation, improved process reliability and greater scalability.
Customer experience and satisfaction are also emerging as important application areas. Solutions powered by natural language processing and GenAI can provide 24/7 multilingual support, improving accessibility and strengthening customer trust.
In addition, water resource sustainability can benefit from GenAI integration in basin management, water reuse planning and dynamic resource allocation. These capabilities allow utilities to anticipate water scarcity scenarios, optimise resource use and reduce environmental impact.
Addressing emerging challenges
According to the report, the greatest value of GenAI lies in its ability to address challenges that are not yet fully digitalised. Six key areas are identified:
• Business resilience — GenAI can transform static contingency plans into dynamic crisis-response tools for climate-related events, cyber incidents and other disruptions, providing real-time guidance and supporting operational continuity.
• Regulatory performance and reliability — Automating compliance monitoring, report generation and multilingual alerts can reduce administrative burdens and minimise the risk of non-compliance.
• Financial viability — GenAI can support capital planning, budget management and data-driven decision-making, helping to strengthen long-term financial sustainability.
• Stakeholder understanding and support — Tailored content such as FAQs, infographics and summaries can be generated for different audiences, improving transparency and helping stakeholders better understand complex decisions without requiring larger communications teams.
• Community sustainability — AI can assist in designing more equitable and sustainable programmes by analysing unstructured community data and modelling the potential impact of different policy scenarios.
• Talent development — With many experienced workers approaching retirement, GenAI can help retain institutional knowledge and accelerate workforce training, reducing reliance on static procedures while fostering a stronger digital culture.
Governance and responsible use
The report also stresses that the adoption of GenAI within utilities requires a rigorous governance framework. According to the study, AI systems “must be transparent, auditable, and allow for human oversight, especially in safety-critical contexts”.
It adds that data protection requirements, including compliance with GDPR and local regulations, alongside risk management and fairness in application design, are essential considerations.
As utilities increasingly integrate AI into critical operations, governance is no longer viewed as an aspirational objective, but as a fundamental requirement for the strategic and sustainable deployment of artificial intelligence.
