AI data centers are consuming massive amounts of water to cool their servers, directly competing with communities for drinking water supplies and threatening public health in water-stressed regions. A single 100-megawatt hyperscale facility can use 2.5 billion liters of water annually, drawing directly from municipal drinking supplies, according to a 2025 report by the UK Government Digital Sustainability Alliance (GDSA). This volume equals the daily water needs of approximately 80,000 people.

The problem is becoming urgent. Two-thirds of U.S. data centers built or in development since 2022 are located in water-stressed areas, creating a collision between AI expansion and environmental limits. When municipal water systems collapse under the strain, the immediate casualties are local sanitation and hospital operations. The UN has formally recognized that human-water systems have exceeded their hydrological limits and sustained irreversible damage, marking what experts call the era of global water bankruptcy.

Why Are Data Centers Using So Much Water?

Data centers consume enormous amounts of electricity to power AI computations, and nearly all of that electricity ends up as heat. Cooling systems remove this heat and release it into the surrounding environment. Traditional evaporative cooling systems, which use water to dissipate heat, have become the standard approach at many facilities. However, this creates a direct trade-off: the more powerful the AI workload, the more heat generated, and the more water required to manage it.

The scale is staggering. Data centers consumed about 485 terawatt-hours of electricity globally last year, representing 1.5 percent of worldwide electricity use. The International Energy Agency (IEA) projects that data center electricity consumption will double to 950 terawatt-hours by 2030, driven largely by specialized AI workloads. This exponential growth in energy demand directly translates to exponential growth in water consumption.

"I would summarise the answer to this question as the three S's: size, speed, and spatial concentration," said Thomas Spencer, an expert at the International Energy Agency, explaining why data centers create such acute local impacts.

Thomas Spencer, International Energy Agency

The problem is compounded by the physical footprint of modern data centers. Unlike traditional industrial facilities, hyperscale AI data centers cluster tightly together and locate themselves near urban populations. These facilities expand from initial announcements to fully commissioned gigawatt-scale campuses in just two to three years, severely outpacing the decades-long planning cycles required to upgrade municipal electrical transmission grids and water infrastructure.

What Solutions Are Experts Proposing?

Reacting to public pushback, the technology industry is developing less resource-intensive cooling systems. However, each approach involves difficult trade-offs that require careful policy guidance:

• Closed-loop cooling systems: Many hyperscale developers have begun implementing closed water systems in new facility designs, which drastically cut water consumption compared to traditional evaporative cooling. However, these systems require facilities to consume more electricity to cool the hardware, creating an environmental trade-off between water savings and increased power usage.
• High-temperature liquid cooling: Breakthrough architectures now utilize liquid coolants operating at 45 degrees Celsius, allowing facilities to manage heat without activating mechanical chillers. These systems can also enable developers to recover waste heat for neighboring residential buildings, transforming a major energy liability into a community asset.
• Regulatory barriers to entry: According to the UK GDSA report, policymakers should adopt a water protocol that requires data center operators to secure non-potable water sources or invest heavily in dry-cooling architecture before receiving construction permits.
• Comprehensive life-cycle management: Solutions should consider siting and infrastructure decisions, operational strategies, and full life-cycle management of hardware and equipment, along with transparent reporting on carbon, water, reliability, and environmental impacts.

Despite these advancements, industry experts note that such innovations remain geographically dependent. Facilities in warmer regions still require chillers during peak summer heat, limiting the effectiveness of some cooling innovations.

How Can Communities and Policymakers Protect Water Supplies?

The stakes are high. Communities view some AI data centers as a direct threat to public health. When municipal water systems collapse under the strain, the immediate casualties are local sanitation and hospital operations. The UN has urged states to formally recognize the water bankruptcy crisis and adopt proactive policies rather than relying on crisis management tools alone.

"There has been a real lack of transparency and a lot of secrecy around some of these data centres," explained Molly Webb, CEO of the NGO Energy Unlocked, highlighting a key barrier to community engagement and informed policymaking.

Molly Webb, CEO, Energy Unlocked

Cities including Denver, Minneapolis, and Seattle are already considering municipal restrictions on data centers. According to Data Center Watch, a research project from technology company 10a Labs, more than 140 local groups have managed to block or delay more than $60 billion in data center investments in roughly a year. This grassroots opposition reflects growing awareness of the local environmental costs of AI expansion.

Experts emphasize that solutions require coordination between multiple stakeholders. Cities and industry leaders should work together on better facility design and neighborhood cooling strategies. Policymakers need to establish clear water protocols before granting construction permits, requiring operators to demonstrate non-potable water sources or invest in dry-cooling systems. Transparent reporting on environmental impacts, including water consumption, is essential for informed decision-making.

The challenge ahead is clear: AI's explosive growth offers tremendous potential benefits to society, but only with ongoing policy-guided investments and concerted effort can we ensure that AI expansion does not worsen the global water crisis or exacerbate inequality in water-stressed communities.