Artificial intelligence may become one of the world’s largest consumers of energy and resources by the end of the decade, according to a new United Nations report that highlights the growing environmental costs of AI technologies.
The report estimates that AI-related energy consumption could double by 2030, accounting for nearly 3 per cent of global electricity use.
AI boom may increase resource consumption
The study challenges the assumption that more efficient AI models will automatically reduce environmental impact.
Instead, it points to the economic concept known as the “Jevons paradox”, where greater efficiency lowers costs and encourages wider adoption, ultimately increasing overall resource consumption rather than reducing it.
According to researchers, as AI tools become cheaper and more powerful, demand for their use is expected to rise sharply across industries.
Data centres under scrutiny
The report notes that data centres already consume enormous amounts of electricity and water.
By 2030, AI-driven infrastructure could require trillions of litres of water annually for cooling purposes while generating emissions comparable to those of entire nations.
Researchers warn that the expansion of data centres will place increasing pressure on energy grids, water resources and land use worldwide.
Concerns over inequality
The UN report also highlights a growing global imbalance in AI infrastructure.
Most AI cloud computing capacity is concentrated in a small number of countries, particularly the United States and China, raising concerns about a widening digital divide.
Meanwhile, environmental costs associated with mineral extraction, electronic waste and resource consumption are often borne by other regions.
Call for responsible AI development
The report urges governments, technology companies and policymakers to adopt more sustainable AI practices.
Recommendations include greater transparency regarding energy use, environmental disclosures, responsible sourcing of materials and stronger integration of AI demand into climate and energy planning.
Experts argue that future AI development must balance innovation with environmental stewardship to ensure technological progress does not come at the cost of long-term sustainability.