As Europe emerges from record-breaking summer temperatures, and as the US prepares for midterm elections in November, data centers find themselves in the firing line on both sides of the Atlantic.
In the UK, water companies say data centers are using 6.6 million liters of precious public supplies every day; in the US, some voters are blaming rises in their electricity bills on, you’ve guessed it, data centers . Bloomberg has described the data center “backlash” as a “defining midterms issue”.
And so, a narrative has been allowed to develop – that too many data centers are being built, and too quickly, and worst of all in areas where water is scarce. No wonder some communities believe their water needs are being ignored in the name of advancing IT infrastructure to support AI.
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In some cases, there has been genuine cause for grievance – in an earlier era, water efficiency was not always a design constraint on data center construction.
But the public debate is now running on figures which range from outdated to plain wrong. Some of the loudest claims overstate the problem by orders of magnitude. Others, including several the industry itself repeats, understate it.
Getting the numbers right matters – and most of all to the communities that host these facilities – because bad numbers produce bad siting decisions, misdirected scrutiny, and misplaced trust.
The No.1 myth about water use
“Every ChatGPT conversation drinks a bottle of water” is the most famous quote in the public discourse about AI infrastructure and data centers. But the claim is not supported by anyone – not even its author. Traced to a single academic paper – Making AI Less “Thirsty” by Pengfei Li, Jianyi Yang, Mohammad A. Islam, and Shaolei Ren of UC Riverside – the figure was a calculated estimate built from public data, not an actual meter reading from a data center.
But a 2024 Washington Post analysis ensured the figure went viral. Since then, Ren has indicated that the GPT-4 estimate was likely far too high and that the real figure is closer to 15ml per prompt in total, of which 5ml is on-site cooling water in a data center. Then in August 2025, Google found that a median text prompt of its AI tool, Gemini, consumed 0.26ml of on-site water – or about five drops.
Credible estimates still span more than a thousandfold depending on model, location, season, and, above all, what you choose to count. But nobody is talking about bottles of water anymore – the honest answer to How much water does a query use? is a range, and the range is wide because disclosure is inconsistent.
Not all data centers are the same
Critics think all data centers are the same when it comes to water and cooling – but that’s simply not the case. Different cooling technologies use different amounts of water. Google disclosed in 2024, for example, that one of its Texas data centers consumed about 10,000 gallons in a year – roughly two months of a single household’s use – while its largest water consumer, in Iowa, used around a billion gallons. Same company, same year, but a difference of five orders of magnitude determined almost entirely by cooling architecture and climate.
There’s another myth that water used by data centers is lost forever. But again, no two facilities are the same. A data center which withdraws river water, runs it through heat exchangers and returns it to the river, at a slightly higher temperature, clearly has a very different impact from one which draws water from an aquifer and evaporates the same volume into the sky. Water withdrawal (and return) and water consumption are two different metrics. Again, bad numbers fail to tell the full story.
Golf is greedier when it comes to water
But are data centers really such water hogs? In most countries, their water use barely registers. In the US, for example, direct annual consumption by data centers accounts for 0.3% of total public supply. By comparison, golf courses use approximately thirty times more water than every American data center combined. And agriculture dwarfs both: the UN’s World Water Development Report puts farming at roughly 70% of global freshwater withdrawals.
National figures, though, obscure local impact. That’s why a single data center drawing millions of gallons of water a day, arriving suddenly in one small municipality, matters more locally than a thousand different water uses spread across a continent. It’s understandable – but important to put in context. Data centers attract community scrutiny not because they are large water users nationally but because they are concentrated and visible.
More AI doesn’t mean more water
The good news is that more AI doesn’t mean more water. The newest data centers have closed-loop designs, immersion cooling, and reclaimed-water agreements, precisely because the thermal loads of next-generation AI demand it.
The three largest hyperscalers – Microsoft, Google, and Amazon – have all committed to being “water positive” by 2030, replenishing more water than they consume. The EU, meanwhile, requires annual water reporting for data centers above 500kW. Regulation has a crucial role to play going forward.
The thirst for facts
On today’s evidence, AI data centers are a small national water user but with a real footprint. However, new engineering, better planning and regulation are achieving results. What is not yet solved is the accounting of water use. Standardized, facility-level and independently verifiable disclosure of withdrawals, discharge, and consumption would cost the industry relatively little and build trust with local communities.
Right now, the bad numbers around data centers and water use create misdirected scrutiny and misplaced trust. That needs to change. Honest accountability matters if public debate and policy are to keep pace with AI’s growth.
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Gabriel Lazar
