Water companies are being asked to do more with less during AMP8. The current regulatory period requires water companies to meet ambitious targets whilst keeping costs down and maintaining ageing infrastructure, and is set against a backdrop of increasing service demands and environmental challenges.
The solution? Innovation will have a crucial role to play in helping water companies meet targets, according to AMP8 recommendations. And whilst rainwater and budget might be scarce right now, the sector has no shortage of the resource that underpins the most innovative, AI-driven solutions: data.
Water companies have vast and varied data estates: from customer interactions and usage records, to water meters and sensors on assets. Locked within these digital assets are valuable insights that can help optimise operations. AI holds the key and is crucial to firstly managing digital assets, and secondly, leveraging data insights to drive crucial efficiencies. There’s more good news: bigger isn’t necessarily better when it comes to AI.
AI holds the keys, and is crucial to firstly managing digital assets, and secondly leveraging data insights to drive crucial efficiencies
Flashy new tools that drain resources are often red herrings. For example, “Agentic AI control rooms” promise to automate asset management, yet it is a grand vision that would require substantial computing power and specialised hardware and software to put into practice. Running and continually updating this technology would also involve significant ongoing investment. There are more realistic solutions that deliver real results.
Rather than total automation, the goal should be to maintain human oversight whilst boosting operational efficiency. The most accessible solutions also leverage and easily integrate with existing systems. Water companies are already seeing real-world results through AI tools that deliver on both fronts.
Having deployed 23,000 sensors with AI-driven analysis to predict sewer blockages, Southern Water is set to cut pollution incidents by up to 40%, for example. Severn Trent is also using AI and predictive modelling of water networks to reduce flooding and overflow spills, and is on track to achieve AMP8’s target for zero serious pollution incidents five years in advance of the deadline. Meanwhile, Yorkshire Water is using data from sensors to flag early signs of deterioration and optimise maintenance scheduling, protecting the environment whilst boosting operational efficiency.
We know there’s no issue around the availability of data. But AI outputs are only as good as the data that models ingest. And the quality and accessibility of organisations’ digital assets is another matter. Where data has been accumulated over decades, gathered via different sources, and stored across different systems, the focus now must be on classifying and cleaning data ready for successful AI adoption. Again, AI can help.
Automating data governance is faster, more effective, and can go a long way towards addressing key water sector priorities. 41% of water industry leaders believe that cost pressures stem from inadequate digital infrastructure. An analysis by Aiimi and the UK Water Partnership also indicates that AI will directly support water companies to achieve AMP8 targets, making it all the more critical that the digital infrastructure needed to support AI solutions is in place.
As AMP8 pushes water companies to do more with less, it’s clear that well-governed data will pay for itself. The path forward lies in smart AI solutions and specific use cases. Big, shiny AI models and unwieldy data estates risk throwing teams off course. But companies that focus on investing in solid data foundations and tools that integrate with existing systems and work alongside teams will be best placed to meet regulatory targets, strengthen resilience, and safeguard vital resources for the future.