AI Data Centers Consume Water and Energy at Unprecedented Rates

Generative artificial intelligence has reshaped how people work, learn, and communicate. The environmental cost of this transformation is now becoming impossible to ignore. Data centers powering AI models consume staggering amounts of electricity and water, creating pressure on infrastructure that was never designed for this scale of demand.

Large data centers can consume up to 5 million gallons of water per day, equivalent to the water use of a town populated by 10,000 to 50,000 people, according to the Environmental and Energy Study Institute. That estimated number matches the combined water usage of Los Alamitos and Seal Beach. In water-scarce regions, this creates direct competition between technology infrastructure and human communities.

The electricity burden is equally concerning. Data centers account for 2.5 to 3.7 percent of global greenhouse gas emissions, exceeding even those of the aviation industry, per 2023 data from Columbia Climate School. By 2026, global data center electricity consumption is expected to approach 1,050 terawatt-hours, which would bump data centers up to fifth place on the global list between Japan and Russia.

Generative AI training clusters consume seven or eight times more energy than a typical computing workload. The power requirements of data centers in North America increased from 2,688 megawatts at the end of 2022 to 5,341 megawatts at the end of 2023, partly driven by the demands of generative AI. (The pace is frankly alarming.)

Once a model is trained, the energy demands don't disappear. Each time a model is used, the computing hardware performs operations that consume energy. Researchers have estimated that a ChatGPT query consumes about five times more electricity than a simple web search. The International Energy Agency reports that a request made through ChatGPT consumes 10 times the electricity of a Google Search.

The physical reality of this infrastructure is becoming visible. The number of data centers has surged to 8 million from 500,000 in 2012. In the tech hub of Ireland, the rise of AI could see data centers account for nearly 35 per cent of the country's energy use by 2026. The heat, the hum of cooling systems, the constant draw on municipal power grids—these are no longer abstract concepts.

There is some movement toward solutions. The MIT Climate Project states that if co-designed with community input, next-generation data centers could lower community electricity costs, improve grid reliability, and remove competition for water resources while avoiding hundreds of millions of tons of CO₂e by 2035. Companies like Google and Meta are already starting to invest in small modular nuclear reactors to power data centers.

The United Nations Environment Programme released an issue note exploring AI's environmental footprint. Golestan (Sally) Radwan, Chief Digital Officer of UNEP, noted that "there is still much we don't know about the environmental impact of AI, but some of the data we do have is concerning." The organization emphasizes that the net effect of AI on the planet must be positive before deploying the technology at scale.

More than 190 countries have adopted non-binding recommendations on the ethical use of AI, which covers the environment. Both the European Union and the United States have introduced legislation to temper the environmental impact of AI. But policies like those are few and far between. Governments are racing to develop national AI strategies but rarely do they take the environment and sustainability into account.

The current infrastructure is heavily based on fossil fuels. To meet all the energy needs, companies are using preexisting coal-fired and methane-powered power plants. The demand for new data centers cannot be met in a sustainable way at the current pace. The bulk of the electricity to power them must come from fossil fuel-based power plants.

AI has integrated itself into society very quickly. Many young people have become dependent on it, as well as many corporations shifting to use AI as a tool and implementing it into their organization's structure. There's no putting AI away now, as much as we may complain and protest.

Public knowledge and public pressure are the things that make change happen. In talking to others, in spreading awareness, in pushing our representatives and being vocal advocates for change, that's how we make these movements actually happen. Whether companies actually prioritize sustainability over speed remains the real question.

Artificial intelligence and its negative impacts are not a hopeless cause, but it's up to everyone to stay involved and actively strive for a better future. The technology isn't going anywhere, so the only option left is to make it work without burning the planet down.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn