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Critics of the AI build-out are picking the wrong fight when they attack data centers for their water use. But they are right when they say the digital economy is getting thirstier and the tech industry should answer for it.
The whole AI supply chain is water intensive, and reducing use in one place can increase it elsewhere. New research shows chip factories and power plants use considerably more water than data centers. Other industries are also more water intensive than AI, though tech is where consumption is increasing the most.
Previous generations of data centers used a lot of water, so it was logical to fear that today’s giant facilities, which generate huge amounts of heat, would suck up large amounts of water for cooling. But hyperscale AI data centers have shifted to more efficient systems that recirculate water or other liquids in closed loops of tubes and pipes. These systems can reduce freshwater consumption at data centers 50% to 70%.
That means, for example, that the first phase of Microsoft’s massive Fairwater data center complex in Wisconsin only needs about four Olympic swimming pools of water annually. That’s half the annual usage of a car wash, according to the Milwaukee 7 Regional Partnership, an economic development organization. It’s only 0.1% of the water Foxconn, the manufacturer that had planned to use the site to make liquid crystal displays, would have been permitted to draw, Microsoft President Brad Smith said at the campus opening.
Data centers can reduce the water they use by eliminating evaporation-based cooling. But this often entails a trade-off: Electricity-hungry equipment has effectively replaced water as the means to keep data centers cool. That moves more of the problem to the electric grid, which uses large amounts of water to cool its power plants.
AI’s power consumption per square foot is quickly growing to as much as 10 times that of traditional cloud-computing. And that gap could rise to 100 times given the power density of the megawatt (1,000-kilowatt) racks Nvidia is designing for the future, well above the 10 to 20 KW racks typical before AI.
Water technology company Xylem and research firm Global Water Intelligence looked at water use across AI’s supply chain, from AI chip foundries to data centers to the portion of power plants allocated to their use. Their January report demonstrates that the water toll of AI is far greater at semiconductor factories and the power plants electrifying chipmaking and computing than at the data centers themselves.
Overall, AI-associated water use will more than double by 2050 from the 6.26 trillion gallons a year withdrawn in 2025, Xylem says. Where we draw water from also matters: 40% of the world’s data centers today are in “areas of high or extremely high water stress,” said the report. And 29% of global chip factories are in “extremely water-stressed areas.”
Interpreting all of this requires a hefty dose of context. The industrial world uses 168.8 trillion gallons of water annually, and this new digital economy—which increasingly helps all other industries operate—comprises just 3.7% of that, said the Xylem report.
Power generation is also getting less water intensive. Coal uses the most water, but it is being phased out. Natural gas, which powers most data centers, is less water intensive. As the power mix pivots to renewables, the water intensity of power generation could fall dramatically.
Another crucial distinction is water consumption versus temporary use: Power plants that use water for cooling return more than 90% of it back to the water system. It may be warmer and it may need treatment to avoid harming ecosystems, but it’s not irrevocably consumed.
Though chip factories use a larger proportion of ultrapure water that they don’t return, they do also return water to the ecosystem. Water technology firm Ecolab, which says wastewater reuse can be as low as 5%, helped a U.S. chip factory save nearly 11 million gallons through improved monitoring and automation.
Increasingly, data center operators are starting to speak up about their water use. “There’s this ongoing narrative that AI is taking all the water. We use, like, zero water,” Chase Lochmiller, CEO of AI infrastructure developer Crusoe, told a Stanford University class last month in a recorded guest lecture. Still, his industry talks a lot less about water used to make power and chips.
Data centers are also getting disproportionate attention relative to everyday water use by agriculture, manufacturing and even lawn care. U.S. golf courses use 531 billion gallons of water a year, and that’s after improving their water efficiency 31% since 2005. U.S. data centers used roughly 17 billion gallons on site in 2023, according to Lawrence Berkeley National Laboratory. Industrial-scale dairy farms, including growing animal feed, are among the most water-intensive operations in agriculture. Critics of dairy farms’ environmental footprint say AI doesn’t come close to that impact.
Still, there’s no doubt we need to find more water as AI grows. A new University of Texas study of AI’s growing water needs in the state found that water withdrawals could rise from 0.75% of demand in 2025 to between 3% and 9% by 2040, depending on how many data centers get built.
The place to find water is obvious-–around 30% of the world’s water is currently lost from public utility networks due to leaks and theft. The water utilities in charge of fixing that issue are typically among the most cash-starved of municipal institutions.
Tech companies are stepping in to provide money and technology. Microsoft is partnering with communities where it is active in Phoenix and Las Vegas to install high-tech water leak detection systems. The technology, which comes from FIDO Tech, runs data captured by sensors through AI to isolate leaks so they can be repaired.
Without that technology, water utilities need to upgrade whole sections of their networks, which can be too costly—so the leaks continue. “At the end of [the] day,” said Al Cho, Xylem’s chief strategy and external affairs officer, “water security is an information problem.”
