The credit rating agency Moody's has warned that water companies face an "elevated" risk from cyber attackers targeting drinking water, as suppliers wait on permission from the industry regulator to ramp up spending on digital security. Moody's said, in a report to investors, that hackers are increasingly zeroing in on infrastructure companies, including water and wastewater treatment companies, and the use of AI (artificial intelligence) could accelerate this trend. Last month, Southern Water, which supplies 4.6 million customers in the south of England, said the Black Basta ransomware group had claimed to have accessed its systems, posting a "limited amount" of data on the dark web. Separately, South Staffordshire Water apologised in 2022 after hackers stole customers' personal data. Moody's warned that the growing use of data-logging equipment to monitor water consumption, and the use of digital smart meters, made companies more vulnerable to attacks.

Nearly 1,000 "dark discharges" of untreated sewage from two water company treatment plants in England have been detected by scientists using artificial intelligence to map spills. The use of machine learning to shine a light on the scale of pollution from untreated effluent being spilled into rivers could be a crucial tool in efforts to improve the quality of rivers, a paper says. Prof Peter Hammond, visiting scientist at the UK Centre for Ecology and Hydrology, who co-authored the paper published in the journal Clean Water, used artificial intelligence to analyse data from two unidentified water companies' waste treatment works from 2009 to 2018. The AI identified 926 "dark discharges" – or previously unknown spills – from the storm overflows at the two treatment plants. Discharges of untreated sewage from storm overflows, or CSOs, are permitted only in exceptional circumstances, such as extreme rainfall, the European commission has ruled.

The Living Planet Index produced by WWF estimates that wildlife population sizes have dropped by 68 per cent since 1970. The charity advocates the use of artificial intelligence (AI) as a tool of conservation technology to monitor and curb this alarming rate of decline. One of the most useful applications is in acoustic monitoring, recording the sounds of wildlife ecosystems on weatherproof sensors. Many animals, from birds and bats to mammals and even invertebrates, use sound for communication, navigation and territorial defence, providing reams of rich data on how a species population is doing. AI provides a fast and cost-effective way to analyse hours of recordings for patterns of behaviour.

The National Water Services Commission (SPAN) acts as a watchdog in ensuring all the different water provider companies meet the need requirements when it comes to quality of water and maintenance. At the same time, SPAN is also looking at ways in which they can ensure the supply of water is consistent and able to monitor pipelines for faults and repair them with minimal impact to the supply. In a move to conserve water in Malaysia, they are also pushing for rainwater harvesting to meet the growing demand for water, especially during drought seasons. In order to achieve this, SPAN believes water companies need to digitally transform their infrastructure, so they are able to meet the demands of the industry. A lot of these companies have ageing infrastructure and rising urbanisation to deal with.

But as these organizations grapple with growing demand, erratic temperatures, aging infrastructure, and the threat of cyberattacks, many struggle to maintain a high level of service in an uncertain and unpredictable landscape. Artificial intelligence (AI) and machine learning (ML), as powered by big data, have the potential to modernize energy and utilities organizations by identifying ways to reduce waste and redundancy, protect and manage assets, and detect performance anomalies – all while realizing valuable cost savings, both for the organization and the customer. In this blog, we explore the three main areas where AI is making a mark on the energy and utilities sector today and how such investments may impact the future. Each year in the U.S. alone, trillions of gallons of water are lost due to aging pipes, broken water mains, and faulty meters. Replacing the entire system would be massively expensive, time-consuming, and impractical, which means that utility companies must take a localized approach to repairs.

Everybody expects to have clean drinking water. But as the lead crises in Michigan has shown, that's not always the case. Now American Water, the largest publicly traded water company in the country, is actively researching the use of machine learning and real-time streaming data technology to detect and identify potentially harmful chemical signatures in its surface drinking water supply. The company is in the early stages of building such a machine learning system. But according to American Water Senior Technologist John Kuchmek, the potential benefits of training machine learning models on real-time water quality data collected by remote sensors are too great to ignore.