Ofwat published its first artificial intelligence adoption plan for the water sector on 15 June 2026, detailing how utilities can deploy AI safely during the regulatory transition in England and Wales. The framework shifts the industry focus from whether to use AI to how it can improve leakage detection, network optimisation and regulatory reporting without compromising accountability.
Operational shifts and accountability
The regulator expects AI to reshape operational and analytical roles rather than replace them outright. Ofwat said AI must not replace professional judgement. The regulator added that "water companies will remain accountable for decisions and outcomes supported by AI systems." This means operations teams will use AI as a support tool for maintenance and forecasting, not as an autonomous decision-maker.
Data quality remains the primary barrier
Early engagement with water companies reveals that poor data readiness restricts the value organisations can extract from AI tools. Inconsistent telemetry and limited data granularity currently block effective deployment. For operations teams managing these datasets, building data quality protocols is a necessary step before deploying predictive models, a standard requirement for any AI Learning Path for Operations Managers.
Emerging use cases in wastewater and demand forecasting
The regulator highlighted growing use cases in wastewater operations. Machine learning models now analyse historic asset data, rainfall forecasts and telemetry to predict sewer blockages, pollution incidents and storm overflow risks. This allows operational teams to move from reactive maintenance to preventative intervention - a shift that requires reliable inputs. The rollout of 10 million smart meters between 2025 and 2030 will further support AI applications in water efficiency and demand forecasting.
Why this matters for operations professionals
Operations teams in the water sector must prepare their data infrastructure now to capture the benefits of predictive maintenance. The Ofwat roadmap makes it clear that accountability for AI-driven outcomes rests with the utility, not the software vendor. Professionals should focus on integrating tools that augment human judgement while ensuring telemetry meets strict quality standards. You can read the full Ofwat AI adoption plan for detailed regulatory expectations.
Your membership also unlocks:
