Could AI Consume More Power Than We Think By 2030? UN Report Sounds Alarm

Artificial intelligence could double its electricity consumption by 2030, accounting for nearly 3 per cent of global power use and generating greenhouse gas emissions comparable to those of the United Kingdom, according to a new United Nations (UN) report.

The report also cautioned that AI-driven infrastructure may consume more water for cooling purposes than the annual drinking water requirements of the world’s population.

According to the report, the growing adoption of AI could lead to the ‘Jevons paradox’, where efficiency improvements result in greater overall resource consumption rather than reductions.

The concept was first observed by economist William Stanley Jevons in 19th-century England, when more efficient coal use lowered costs and ultimately increased overall demand.

The report noted that as AI models become cheaper and more accessible, new applications and higher usage volumes are likely to emerge, offsetting gains achieved through efficiency improvements.

To address these concerns, the UN proposed a roadmap for responsible AI development based on transparency, efficiency by design, equity and justice, lifecycle responsibility, global cooperation, and sustainable use.

The report highlighted that data centres consumed as much electricity as Saudi Arabia last year.

If power consumption doubles by 2030, the resulting carbon footprint would require 6.7 billion trees grown over a decade to offset emissions. It further estimated that data centres could require around 9.3 trillion litres of water and land, nearly ten times the size of Mexico City, to support future growth.

Concerns Over a Widening Global Divide

The report also warned of a widening digital and environmental divide, noting that only 32 countries host AI-specific cloud infrastructure, with 90 per cent of the capacity concentrated in the United States and China. It urged routine environmental disclosures at both the model and task levels, stressing that responsible AI requires governance across the entire value chain, from mineral extraction and sourcing to recycling and safe disposal.

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