Artificial intelligence has become part of everyday life at an astonishing pace. It helps write emails, generate images, answer questions, recommend videos, and even assist with medical research. While much of the conversation around AI focuses on its creativity and convenience, a less visible side of this technology is beginning to raise serious environmental questions.
New research suggests that the recent surge in artificial intelligence development may be leaving behind a climate footprint comparable to that of one of the largest cities in the United States. In fact, the total carbon emissions linked to AI activity in 2025 may rival those produced by New York City over the same period.
This revelation highlights a growing concern. As AI systems become more powerful and widespread, their hidden environmental costs are becoming harder to ignore.
How Big Is AI’s Climate Impact Really
A study published in the academic journal Patterns estimates that artificial intelligence operations in 2025 could generate as much as 80 million metric tonnes of carbon dioxide emissions. To put that number into perspective, it is roughly equivalent to the annual emissions of New York City.
This research was conducted by Alex de Vries Gao, a Dutch researcher and the founder of Digiconomist, a platform that tracks the environmental impact of digital technologies. According to his calculations, AI systems now account for more than 8 percent of the total emissions produced by global aviation.
For a technology often described as virtual or cloud based, this physical footprint may come as a surprise. Yet behind every AI response lies a network of massive computers running around the clock, consuming electricity and requiring cooling systems that often depend heavily on water.
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The Water Cost of Intelligence
Carbon emissions are only part of the story. The same study estimates that AI related water consumption could reach 765 billion liters in 2025 alone.
This water is primarily used to cool the data centers that power artificial intelligence systems. These facilities generate enormous amounts of heat as servers process vast quantities of information. To prevent overheating, water based cooling systems are often employed, sometimes in regions already facing water stress.
Unlike household water use, which people can see and regulate, the water used by AI infrastructure is largely invisible to the public. This makes it easier for the environmental cost to remain overlooked, even as demand for AI services continues to grow.
Separating AI From General Data Centers
One of the most significant aspects of this research is its attempt to isolate AI emissions from broader data center activity. In the past, it has been difficult to determine how much environmental impact can be directly attributed to artificial intelligence versus general cloud computing.
De Vries Gao argues that these findings represent the first robust estimates that specifically focus on AI systems. By using data from technology companies’ own disclosures, the study paints a clearer picture of how much energy and water are being consumed to support machine learning models, large language systems, and generative tools.
This distinction matters because AI is growing far faster than other digital services. Without targeted measurements, its impact risks being underestimated or lost within broader infrastructure statistics.
Who Benefits and Who Pays the Price
A central argument of the study is that while AI delivers massive economic value to large technology firms, the environmental costs are shared by society as a whole.
Consumers benefit from smarter tools and more efficient services, but they rarely see the emissions or water usage that make these conveniences possible. Meanwhile, tech companies continue to expand AI capabilities at record speed, driven by competition and market demand.
Critics argue that this creates an imbalance. The profits are concentrated among a few of the world’s richest corporations, while the environmental consequences are distributed globally, affecting air quality, water resources, and climate stability.
The Scale of AI Infrastructure Expansion
The growth of artificial intelligence is closely tied to the rapid expansion of data centers. According to the International Energy Agency, some of the largest AI focused data centers currently under construction are expected to consume as much electricity as two million households each.
The majority of this new energy demand is concentrated in the United States, China, and Europe, where AI development is most intense. These facilities require constant power, high speed connectivity, and reliable cooling, making them some of the most resource intensive buildings ever created.
As more countries race to become leaders in artificial intelligence, the number of these mega data centers is expected to rise even further.
A Closer Look at the United Kingdom
The environmental impact of AI infrastructure is already becoming visible at the national level. In the United Kingdom, a planned Google data center in Blyth is projected to emit more than 180,000 tonnes of carbon dioxide each year.
This single facility illustrates how localized emissions can add up quickly. While companies often emphasize efficiency improvements and renewable energy investments, the sheer scale of operations means that emissions remain substantial.
Communities near these sites may experience increased strain on local energy grids and water supplies, raising questions about long term sustainability.
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The Situation in Developing Regions
The environmental risks may be even greater in countries where energy systems rely heavily on fossil fuels. In India, for example, new data center projects often depend on diesel powered backup generators to ensure uninterrupted operation.
Environmental analysts warn that this reliance could lead to massive carbon liabilities as AI infrastructure expands. Diesel generators are among the most polluting forms of backup power, and their widespread use could significantly increase emissions in regions already grappling with air quality challenges.
This raises concerns about whether AI growth could deepen global environmental inequalities, with developing nations bearing a disproportionate share of the pollution.
Calls for Transparency and Accountability
Advocacy groups are increasingly calling for greater transparency from technology companies regarding the environmental impact of artificial intelligence. One such group, Foxglove, argues that the public is effectively footing the environmental bill for AI expansion without adequate disclosure or oversight.
Critics point out that some companies have omitted key information from their sustainability reports, particularly regarding water usage linked to AI operations. Without clear data, it becomes difficult for regulators, communities, and consumers to assess the true cost of these technologies.
Greater transparency could also help encourage more responsible design choices, such as investing in cleaner energy sources and more efficient cooling systems.
Why This Conversation Matters Now
Artificial intelligence is still in a phase of rapid growth. The choices made today about how AI systems are built and powered will shape their environmental footprint for decades to come.
If emissions and water use continue to rise unchecked, AI could become a significant contributor to global climate challenges. On the other hand, increased awareness and accountability could push the industry toward more sustainable practices.
The challenge lies in balancing innovation with responsibility. AI has the potential to help address climate problems through smarter energy management, scientific modeling, and resource optimization. Yet without careful oversight, it may also become part of the problem it aims to solve.
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The Invisible Cost of Convenience
For many users, AI feels effortless. A question typed into a chat box or an image generated in seconds does not appear to consume physical resources. But behind each interaction is a complex network of machines drawing power, using water, and producing emissions.
Understanding this hidden cost does not mean rejecting AI altogether. Instead, it invites a more thoughtful conversation about how technology is developed, who benefits from it, and how its impacts are managed.
As artificial intelligence continues to reshape modern life, its environmental footprint deserves the same level of attention as its technical capabilities. Only then can society make informed decisions about the future of this powerful tool.
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