AI may use enough water to match needs of 1.3 billion people by 2030

Artificial intelligence (AI) may be powering and transforming our everyday lives, but is exacting a huge cost in terms to natural resources too. By 2030, data centres, the global infrastructure powering AI, could use enough water to match the needs of 1.3 billion people, the United Nations has warned.

Data centres could consume 945 terawatt-hours of electricity annually by 2030, nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria, countries collectively home to more than 650 million people.

However, this is just the tip of the iceberg. On top of the carbon footprint, every unit of electricity used by data centres also carries a ‘water footprint’ for cooling and energy production, and a ‘land footprint’ associated with power generation and supply chains. By 2030, the three countries’ associated water footprint will equal the basic annual domestic water needs of all 1.3 billion people in Sub-Saharan Africa, and their land footprint will exceed 14,500 square kilometers, roughly twice the Jakarta metropolitan area, home to more than 32 million people.

A recent report – Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints – by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) has, perhaps for the first time, highlighted a critical gap in how AI’s environmental impact is measured. Greenhouse gas emissions, particularly those linked to training large models, tend to be prioritised, but this approach overlooks other environmental costs.

Solutions seen as ‘green’ in one sense may worsen pressures in others, particularly in regions already facing resource scarcity. For example, switching to certain renewable energy sources may reduce carbon emissions but can significantly increase water consumption and land use.

Researchers have previously warned about the greenhouse gas emissions of data centers before. But, the UN scientists now argue that the environmental costs of AI and data centers cannot be understood through carbon emissions alone. In the report, they quantify the carbon, water and land footprints of AI’s electricity use across the globe and highlight the big differences between these footprints in the world’s 20 largest data center hubs.

“This report is not a case against artificial intelligence, a technological transformation that is improving the lives of billions of people around the world,” said Professor Kaveh Madani, Director of UNU-INWEH who led the investigation team.

“It is a call for using it responsibly and addressing its unintended impacts proactively to make it sustainable and equitable. We have a narrow window to ensure that the backbone of the technological revolution of our era develops within planetary limits, and that the communities who provide the critical minerals for advancing AI and the ones that host its infrastructure and e-waste are also among those who benefit from it.”

The environmental impacts of AI infrastructure are not evenly distributed. While the benefits of the technology are global, its costs are often concentrated in specific regions, the repost states.

In some countries, data centres already account for a significant share of national electricity consumption, placing pressure on energy systems. In others, expanding facilities are drawing heavily on water supplies, sometimes amid drought conditions.

The benefits and burdens of the massive global expansion of AI are highly unequal. Several site-level cases in the report show how globally distributed AI services create intense local pressures. In Ireland, data centers accounted for 21 per cent of total metered electricity in 2023, exceeding all urban households.

The national grid operator has paused new approvals around Dublin until 2028, making Ireland a concrete, documented example of what happens when AI infrastructure growth outpaces energy planning—and a preview of what other countries are heading toward.

In Querétaro, Mexico, expanding compute infrastructure is drawing on water supplies amid prolonged droughts. In Uruguay, plans for a water-intensive data center coincided with a 2023 drought that depleted Montevideo’s freshwater reserves, making tap water unsafe to drink.

Despite the stark findings, UNU researchers stress that the report is not an argument against AI itself. Rather, it calls for urgent action to ensure that the technology develops within planetary limits.

The study outlines a framework for a “responsible AI ecosystem”, built on principles including transparency, efficiency by design, equity, lifecycle responsibility, global cooperation and sustainable use.

Governments are urged to integrate AI infrastructure into energy, water and land-use planning, while companies are encouraged to design systems that minimise resource consumption. Users, too, have a role to play by choosing lower-impact applications where possible.

Ultimately, the report argues that the future of AI will depend not only on technological innovation but also on governance choices made today.