UN Report Reveals AI Environmental Impact Will Double by 2030 as Data Centers Rival Nations

AI to double data centre power and water consumption by 2030, UN researchers say

SINGAPORE, June 3 (Reuters) - Data centres are expected to consume twice as much power and water by 2030 as they expand to meet the surge in demand from artificial intelligence, U.N. researchers said on Wednesday. Unless governments heed the rising environmental costs of AI, the rapid rollout could also strain scarce land resources and create mountains of electronic waste, the United Nations University Institute for Water, Environment and Health warned in a report. Here are a few takeaways: Reporting by David Stanway; Editing by Sherry Jacob-Phillips Our Standards: The Thomson Reuters Trust Principles., opens new tab

UN calculates nation-sized environmental footprints for AI and data centers

WASHINGTON (AP) -- The environmental footprint of data centers already rivals some of the world's largest countries, according to a United Nations University report, which also predicts their water and energy use and pollution will double in just four years as use of artificial intelligence grows. Last year, global data centers used 448 trillion watt-hours of electricity, more than all but 10 countries of the world, said the report issued Wednesday. That electricity use produced about 208 million tons (189 million metric tons) of carbon dioxide, about the same amount as Argentina, and producing that much energy consumed about 1.2 trillion gallons (4.5 trillion liters) of water, according to the report on the environmental consequences of AI's energy use. By 2030, data centers will account for nearly 3% of the world's projected electricity use, with 935 trillion watt-hours. If data centers were a country, the country would be projected to rank sixth-highest in power use in 2030. That would produce nearly 440 million tons (399 million metric tons) of carbon dioxide, the report said. The study focused on energy use and didn't examine the massive amount of water used to cool data centers. "If you look at these numbers, we're seeing scales comparable to nations," said study co-author Kaveh Madani, a water scientist and director of the United Nations University Institute for Water, Environment and Health in Canada. "The demand is enormous." Much of the growth of data centers is being driven by AI. About 20% of data centers' energy is currently due to AI, but that should grow to 40% by 2030, the report said. First global look at ecological impact The report is significant because of the credibility and authority of the U.N., not just because of any one set of eye-popping numbers, said Fengqi You, a Cornell University energy engineering professor who directs the college's AI sustainability issues. "Its value is that a U.N. institution is putting carbon, water, land, life-cycle impacts and environmental justice into one frame" for an issue that is often shrouded in secrecy and partial disclosures, said You, who was not part of the report. "The general public should be concerned, but not panicked," he added. Jean Su, director of the Energy Justice Program at the Center for Biological Diversity, said the report is important because it is the first U.N., or even global, report "that shines a light on the environmental harms of AI." National Artificial Intelligence Association President Caleb Max emphasized how his industry is becoming more efficient and how it benefits the public: "AI is rapidly becoming part of our everyday lives and adding benefits that improve safety, live longer, work more efficiently, enhance food production, and reduce poverty. The evidence is growing daily that the energy return on investment of AI development is transformative for our world and therefore more than worth it." Josh Levi, president the Data Center Coalition, said the industry takes its environmental impact seriously. "We remain committed to working with policymakers, local communities, and industry partners to ensure that as data centers grow, they do so responsibly, transparently, and in ways that reflect the best available practices," he said in a statement. How much energy your query uses and how to trim it Madani, also the winner of the most recent of the Stockholm Water Prize, said the numbers show the environmental cost of AI, which may seem cleaner at first glance than other mechanical devices, such as cars and furnaces, that have visible pollution. "AI is not just a virtual thing. We're talking about something that has physics, something that has real impacts. There is infrastructure there. There is energy that is being used," Madani said. "A lot of hardware is behind all these operations that to us seem very, very clean because we don't see smoke out of our devices. On our cellphone, there is no visible smoke or out of our computer or something. But somewhere else someone is suffering." People can reduce AI's massive energy appetite by being less polite and more concise in their queries, Madani said. The report found that cutting word use in requests by 30% can reduce energy used by AI by 25%. That would save about the same amount of electricity as what about 700,000 people in Africa use in a year, the report said. "If you're too polite, then that extra 'please' you put there can make a huge difference," Madani said. "You've got to be very precise and be short." A typical ChatGPT-style query is about 200 times more energy-intensive than the type of basic text classification used in an email spam filter, for example. AI-generated images or video require much more energy. And the more complicated the AI, the more energy it takes to train or learn. The report said GPT-3 used about 1.3 billion watt-hours to train, but the next version used 50 to 70 billion watt-hours. But it's not training that really feasts on power, said study co-author Miriam Aczel, a United National University environmental policy researcher. About 90% of the power use of AI comes from operational requests, she said. GPT alone accounts for 2.5 billion prompts a day, she said. Efficiency still means more power use Even though tech advocates can argue that their machines are becoming more efficient, there's a common paradox that finds when things get more efficient, they are used more often and total energy use soars even if individual uses are more efficient, Madani said. While some companies tout the use of renewable energy for data centers, Madani said that means the supply of clean electricity is depleted and thus dirtier energy is used elsewhere. One of the problems in conducting this study is that many companies and places are not transparent about what data centers and AI are consuming or even where and how big they are, Aczel and Madani said. "We cannot manage what companies do not disclose," Cornell's You said. ___ The Associated Press' climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP's standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org.

AI Could Use as Much Water as 1.3 Billion People by 2030

The water used by artificial intelligence is expected to equal the needs of 1.3 billion people by 2030 -- threatening natural resources for billions around the world. That's according to a new report from the United Nations University Institute for Water, Environment and Health (UNU-INWEH) which quantifies the carbon, water, and land footprints of AI's electricity use around the globe. The report finds that AI's environmental cost is often mismeasured -- focusing solely on carbon emissions. However, cooling and generating power for data centers comes with a "water footprint," while the energy infrastructure and supply chains to build the data centers have a "land footprint." These are important factors to consider, the report says, when analyzing the stressors a region might be facing due to data centers. By 2030, the report finds, global data centers powering artificial intelligence are projected to consume 945 terawatt-hours of electricity. This is nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria -- countries that together are home to more than 650 million people. The water footprint of data centers is projected to equal the basic domestic water needs of all 1.3 billion people in Sub-Saharan Africa for a year, while their land footprint could exceed 5,590 square miles, roughly twice the Jakarta metropolitan area that's currently home to more than 32 million people. But switching to cleaner sources of energy isn't as simple as it sounds. Minimizing one footprint could come at the expense of magnifying another, researchers say. For example, switching from coal to bioenergy cuts electricity's carbon footprint by 70% -- but increases its water footprint more than 30-fold and its land footprint 100-fold. "What surprised us most is how often the choices that look greenest from a carbon perspective end up worse for water or for land," Miriam Aczel, UNU-INWEH researcher and the lead author of the report, said in a press release. "If we keep judging AI sustainability by carbon alone, we might think that renewables make AI infrastructure clean but that is solving one problem while creating other problems, often in places that didn't ask for it." For a number of communities around the globe, AI is already using up significant energy resources. In 2025 alone, data centers consumed an estimated 448 terawatt-hours of electricity, the report found -- more than the country of Saudi Arabia. In many cases, this excessive energy use comes at a cost to those who reside near them. In Ireland, data centers accounted for 21% of total metered electricity in 2023, exceeding electricity use by urban households. (The country's national grid operator has since paused new approvals around Dublin until 2028.) Large data centers can consume up to 5 million gallons per day to keep servers cool. In communities already facing water scarcity, this risks putting a strain on already sparse resources. In Querétaro, Mexico, plans for fast-tracked data centers stand to jeopardize water supplies amid prolonged droughts. Uruguay saw a similar battle after plans to build a water-intensive data center were announced during a 2023 drought that depleted freshwater reserves in the country's largest city, making tap water unsafe to drink -- sparking protests over the prioritization of industrial demands over human needs. In addition to the strain on resources and impact to local environments, there is a separate inequality at play, the report notes. As data centers continue to explode around the world, the researchers warn of a widening "digital divide," in which wealthier countries are able to invest in AI infrastructure while lower-income nations struggle to access and participate in the AI economy. In some ways, this divide is already apparent. As of 2025, only 32 countries -- 16% of nations -- host AI-specialized data centers, and 90% of that capacity is concentrated in two countries: the U.S. and China. Moreover, AI infrastructure could generate up to 2.5 million metric tons of electronic waste each year by 2030, which could expose frontline communities -- predominantly in low-income countries where many countries export their waste -- to toxic substances. "The concentrated development of AI infrastructure in the privileged areas of the world is creating a large digital divide that poses profound challenges in the equitable development of AI," Tshilidzi Marwala, rector of the United Nations University and Under-Secretary-General of the United Nations, said in a press release. "AI can certainly advance prosperity and human well-being. Whether it does so equitably is now a governance question, not a technical one." To ensure that data center development doesn't come at a cost to communities, the report calls for a "responsible AI ecosystem," and notes that permitting, environmental impact assessment, and community consultation should reflect the reality of water and land use along with carbon. Governments, investors, and financial institutions must implement the guardrails that will minimize environmental consequences, said Kaveh Madani, director of UNU-INWEH. "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."

UN urges AI firms to reveal environmental footprint

Paris (France) (AFP) - A UN report on Wednesday urged artificial intelligence firms to disclose their environmental footprint, warning that the AI boom is putting growing pressure on power grids, water supplies and land resources. The study also urged governments to require standardised environmental reporting from AI providers, and called on users to choose less energy-intensive tools that can accomplish the same task. "What we are showing here is probably just the tip of the iceberg," Kaveh Madani, director of the United Nations University Institute for Water, Environment and Health (UNU-INWEH), told AFP. "We need to require more transparency. We need the providers to provide that information," Madani said. The authors of the report, "Environmental Cost of AI's Energy Use: Carbon, Water and Land Footprints", used primary data from a range of sources to make their estimates, Madani said. 'Not an anti-AI report' The global AI market is expected to grow from $189 billion in 2023 to $4.8 trillion by 2033, the UNU-INWEH report said. Data centres, the warehouses of servers that power AI and other digital services, consumed 448 terawatt-hours (TWh) of electricity in 2025. If data centres were a country, their consumption would have ranked in 11th place -- just under France with 468 TWh, the study said. AI workloads accounted for a fifth of the total electricity use at data centres last year, and they are expected to rise to 40 percent by 2030. Consumption by data centres is projected to exceed 945 TWh by 2030, ranking sixth among countries and emitting 399 million tonnes of CO2 equivalent. By comparison, the UK's net emissions reached 367 million tonnes last year. The report cautioned that reducing carbon emissions did not automatically reduce water or land impacts. Data centres could guzzle 9.32 trillion litres of water by 2030, enough to meet the annual basic water needs of the entire population of sub-Saharan Africa, the report said. The land they occupy would be 18 times bigger than New York City. ChatGPT alone is estimated to process around 2.5 billion prompts per day, translating into roughly 383 GWh of electricity a year -- enough to meet the annual demand of nearly three million people in sub-Saharan Africa, the report said. AI videos are the the most energy-hungry product. A single short AI-generated clip can draw as much electricity as hundreds of AI-generated images. The report also warned of a growing digital divide, with most AI-specialised data centres located in the United States, China and the European Union while many developing countries bear environmental costs linked to mineral extraction and waste disposal. "This is not an anti-AI report," Madani said. "We are simply saying that we have to proactively monitor their impacts to be able to curb them, to be able to control them before it's too late." Chatbot or cookbook? The report said AI developers and service providers should "make the invisible visible" by publishing clear, standardised accounts of energy and environmental footprints for training models and generating responses for users. AI firms should also improve efficiency of their systems. "Governments and regulators should treat environmental disclosure for AI as routine," it said. Government climate and energy plans should incorporate growing AI demand while efforts should be made to keep data centres away from water-stressed regions. But individual users should also avoid using AI for tasks that could be done with conventional tools, the authors said. "All of us can make a huge difference," Madani said. The report estimates that a single AI‑enhanced internet search may use 10 times more energy than a conventional search. "Do you need ChatGPT to give you a recipe" or "(do) you have a cookbook that's sitting on your kitchen counter that you could just open?" UNU-INWEH co-author Miriam Aczel told AFP. "There are a lot of simple behavioural tweaks that people can make that can help reduce their footprint," she said. "But I think all of this starts with knowledge, information and disclosures."

UN Calculates Nation-Sized Environmental Footprints for AI and Data Centers

WASHINGTON (AP) -- The environmental footprint of data centers already rivals some of the world's largest countries, according to a United Nations University report, which also predicts their water and energy use and pollution will double in just four years as use of artificial intelligence grows. Last year, global data centers used 448 trillion watt-hours of electricity, more than all but 10 countries of the world, said the report issued Wednesday. That electricity use produced about 208 million tons (189 million metric tons) of carbon dioxide, about the same amount as Argentina, and producing that much energy consumed about 1.2 trillion gallons (4.5 trillion liters) of water, according to the report on the environmental consequences of AI's energy use. By 2030, data centers will account for nearly 3% of the world's projected electricity use, with 935 trillion watt-hours. If data centers were a country, the country would be projected to rank sixth-highest in power use in 2030. That would produce nearly 440 million tons (399 million metric tons) of carbon dioxide, the report said. The study focused on energy use and didn't examine the massive amount of water used to cool data centers. "If you look at these numbers, we're seeing scales comparable to nations," said study co-author Kaveh Madani, a water scientist and director of the United Nations University Institute for Water, Environment and Health in Canada. "The demand is enormous." Much of the growth of data centers is being driven by AI. About 20% of data centers' energy is currently due to AI, but that should grow to 40% by 2030, the report said. First global look at ecological impact The report is significant because of the credibility and authority of the U.N., not just because of any one set of eye-popping numbers, said Fengqi You, a Cornell University energy engineering professor who directs the college's AI sustainability issues. "Its value is that a U.N. institution is putting carbon, water, land, life-cycle impacts and environmental justice into one frame" for an issue that is often shrouded in secrecy and partial disclosures, said You, who was not part of the report. "The general public should be concerned, but not panicked," he added. Jean Su, director of the Energy Justice Program at the Center for Biological Diversity, said the report is important because it is the first U.N., or even global, report "that shines a light on the environmental harms of AI." National Artificial Intelligence Association President Caleb Max emphasized how his industry is becoming more efficient and how it benefits the public: "AI is rapidly becoming part of our everyday lives and adding benefits that improve safety, live longer, work more efficiently, enhance food production, and reduce poverty. The evidence is growing daily that the energy return on investment of AI development is transformative for our world and therefore more than worth it." Josh Levi, president the Data Center Coalition, said the industry takes its environmental impact seriously. "We remain committed to working with policymakers, local communities, and industry partners to ensure that as data centers grow, they do so responsibly, transparently, and in ways that reflect the best available practices," he said in a statement. How much energy your query uses and how to trim it Madani, also the winner of the most recent of the Stockholm Water Prize, said the numbers show the environmental cost of AI, which may seem cleaner at first glance than other mechanical devices, such as cars and furnaces, that have visible pollution. "AI is not just a virtual thing. We're talking about something that has physics, something that has real impacts. There is infrastructure there. There is energy that is being used," Madani said. "A lot of hardware is behind all these operations that to us seem very, very clean because we don't see smoke out of our devices. On our cellphone, there is no visible smoke or out of our computer or something. But somewhere else someone is suffering." People can reduce AI's massive energy appetite by being less polite and more concise in their queries, Madani said. The report found that cutting word use in requests by 30% can reduce energy used by AI by 25%. That would save about the same amount of electricity as what about 700,000 people in Africa use in a year, the report said. "If you're too polite, then that extra 'please' you put there can make a huge difference," Madani said. "You've got to be very precise and be short." A typical ChatGPT-style query is about 200 times more energy-intensive than the type of basic text classification used in an email spam filter, for example. AI-generated images or video require much more energy. And the more complicated the AI, the more energy it takes to train or learn. The report said GPT-3 used about 1.3 billion watt-hours to train, but the next version used 50 to 70 billion watt-hours. But it's not training that really feasts on power, said study co-author Miriam Aczel, a United National University environmental policy researcher. About 90% of the power use of AI comes from operational requests, she said. GPT alone accounts for 2.5 billion prompts a day, she said. Efficiency still means more power use Even though tech advocates can argue that their machines are becoming more efficient, there's a common paradox that finds when things get more efficient, they are used more often and total energy use soars even if individual uses are more efficient, Madani said. While some companies tout the use of renewable energy for data centers, Madani said that means the supply of clean electricity is depleted and thus dirtier energy is used elsewhere. One of the problems in conducting this study is that many companies and places are not transparent about what data centers and AI are consuming or even where and how big they are, Aczel and Madani said. "We cannot manage what companies do not disclose," Cornell's You said. ___ The Associated Press' climate and environmental coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP's standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org.