Concerns about the water and energy demands of data centers have become prolific in recent weeks. But debates about their impact often overlook the rapid advances in cooling technology and cleaner energy that are already having an impact.
However, data centers’ resource consumption should be front and center of the AI conversion, as it is set to grow rapidly. By 2030, data centers’ water and energy consumption will double as AI demand leads to rapid construction of the infrastructure.
But data centers will not cause the world to run out of water or energy. Water- and energy-saving technologies already in use are reducing their impact, while Shanghai’s groundbreaking underwater data center demonstrates how innovative design can limit water, energy and land use.
Data centers have underpinned the internet since its founding. Apps, email, file storage and cloud services all run through them.
Modern AI workloads, however, have transformed their power demands beyond recognition. Today a single AI data center can match the electricity consumption of 100,000 homes, making them a significant drain on local energy grids, especially if a region is susceptible to shortages.
Data centers’ energy consumption is only rising as more are built across the world. In the US, data centers could increase from 4.4% to 12% of national electricity usage by 2028 — that is equivalent to adding eight New York Cities to the American grid.
Data centers also consume large amounts of water in two main ways. Water is used directly to cool servers and storage systems, which generate considerable heat, and indirectly to produce electricity at fossil fuel power plants where it is heated into steam to drive turbines.
In the UK, data centers have been estimated to use up to eight times as much water as average on hot summer days, underlining how their impact can rise when local resources are already under strain.
As the effects of climate change intensify, the location of data centers, and methods to reduce their water and energy consumption, are becoming ever more important.
Fortunately, resource-saving measures are already being implemented. Data centers on land use closed-loop cooling systems that recycle water rather than continually evaporating it. This can reduce freshwater use by up to 70% compared to traditional open evaporative methods.
China has also pioneered a revolutionary new type of data center in Shanghai: wind-powered, and underwater. The facility, which began full commercial operations in May 2026, uses seawater as a coolant instead of using refrigerated fresh water as land-based data centers do, reducing the electricity required to cool the computers.
It uses at least 30% less electricity than traditional data centers, and offshore wind turbines reduce reliance on fossil fuels and cut the data center’s carbon emissions. Innovative solutions such as these will go a long way to reducing data centers’ resource consumption.
AI is also part of the solution to data centers’ draw on resources. AI can optimise electricity grids and shift computing workloads towards periods when cleaner energy is more efficient, making energy use more effective overall. AI can also anticipate fluctuations in demand and adjust energy consumption accordingly, reducing waste.
It might sound obvious, but some areas are just better equipped to accommodate a data center than others. For example, facilities in hot or water-stressed regions will impose a heavier burden on resources than those supplied by cleaner energy with plentiful water and located in cooler climates.
AI’s growing demand for data centers will increase electricity and water consumption, that is true. But it does not mean the technology will exhaust regional or global supplies of either resource.
The AI boom and the infrastructure buildout accompanying it are well underway. To manage its impact, the industry needs to plan ahead. Cleaner energy, efficient cooling, and sites that have significant water and energy supplies will all limit the infrastructure’s drain on resources.
