Artificial Intelligence’s Environmental Costs Threaten Water, Land, and the Climate

 الأراضي المقدسة الخضراء / GHLands

As artificial intelligence continues to expand rapidly across the globe, concerns are growing over its environmental impact, which extends far beyond carbon emissions to include increasing pressure on water resources, land use, and the planet’s natural ecosystems.

According to projections, the data centers powering AI technologies could consume up to 945 terawatt-hours of electricity annually by 2030—roughly three times the combined annual electricity consumption of Pakistan, Bangladesh, and Nigeria, countries with a total population of more than 650 million people.

The environmental footprint of these facilities goes well beyond electricity demand. Their operation also requires vast amounts of water for cooling and energy production, while large areas of land are needed to support the infrastructure and supply chains behind AI systems.

Rethinking Sustainability Metrics

A recent study by the United Nations University found that AI-related water consumption could equal the basic annual household water needs of approximately 1.3 billion people by the end of this decade. At the same time, the land footprint associated with AI infrastructure could exceed 14,500 square kilometers.

The study argues that environmental assessments of artificial intelligence often focus primarily on greenhouse gas emissions while overlooking other critical factors such as water use and land consumption. As a result, some solutions that appear environmentally friendly from a carbon perspective may unintentionally place greater pressure on scarce natural resources, particularly in regions already facing water shortages.

Daily AI Use Drives Most Energy Demand

While public attention often centers on the energy required to train advanced AI models, the study found that everyday use of AI accounts for between 80 and 90 percent of total energy consumption.

Some of the world's most widely used AI services process nearly 2.5 billion prompts every day, requiring hundreds of gigawatt-hours of electricity each year.

Energy demand also varies significantly depending on the task. Generating a single AI-created image can require more than a thousand times the energy needed to classify a simple text, while AI-generated videos consume substantially more computing power and resources.

The report warns that improvements in efficiency alone are unlikely to offset rising demand. As AI systems become faster, cheaper, and more accessible, their growing popularity may ultimately increase overall resource consumption—a phenomenon known as the rebound effect.

Local Environmental Burdens, Global Benefits

The environmental impacts of AI infrastructure are not evenly distributed around the world. While the benefits of artificial intelligence are global, many of its environmental costs are concentrated in specific regions.

In some countries, data centers already account for a significant share of national electricity consumption, placing additional strain on power grids. Elsewhere, expanding facilities consume large quantities of water, even during periods of drought.

The report also highlights the growing challenge of electronic waste, estimating that AI infrastructure could generate up to 2.5 million metric tons of e-waste annually by 2030. Much of this burden is expected to fall on lower-income countries that lack adequate systems for the safe disposal and recycling of electronic waste.

In addition, the extraction of critical minerals needed to manufacture AI hardware raises concerns about environmental degradation and social inequality in mining regions.

A Growing Global Digital and Environmental Divide

The study also found that more than 90 percent of the world's specialized AI computing capacity is concentrated in just two countries—the United States and China—while more than 150 countries have little or no significant domestic AI infrastructure.

Researchers argue that this imbalance is not only an economic issue but also an environmental justice concern, as some countries bear environmental costs without receiving an equitable share of the technological and economic benefits generated by artificial intelligence.

Toward More Responsible Artificial Intelligence

Despite these findings, the researchers emphasized that the study is not intended to discourage the development of artificial intelligence. Instead, it calls for urgent action to ensure that AI evolves within the environmental limits of the planet.

The report proposes a framework for responsible AI based on transparency, resource efficiency from the design stage, fairness, accountability throughout the technology's lifecycle, international cooperation, and sustainable deployment.

It also urges governments to integrate AI infrastructure into national planning for energy, water, and land use, while encouraging technology companies to design systems that consume fewer resources. At the same time, users are encouraged to choose AI applications with lower environmental impacts whenever possible.

The report concludes that the future of artificial intelligence will depend not only on technological innovation but also on the governance decisions made today to ensure that AI develops in a way that is environmentally sustainable and socially responsible.