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The Guardian - UK
The Guardian - UK
Technology
Fiona Harvey Environment editor

Energy demands from AI datacentres to quadruple by 2030, says report

A series of people in silhouette on devices under the words 'AI Artificial Intelligence'
In the US alone, processing data is expected to consume more electricity than all other energy-intensive goods combined by 2030. Photograph: Dado Ruvić/Reuters

The global rush to AI technology will require almost as much energy by the end of this decade as Japan uses today, but only about half of the demand is likely to be met from renewable sources.

Processing data, mainly for AI, will consume more electricity in the US alone by 2030 than manufacturing steel, cement, chemicals and all other energy-intensive goods combined, according to a report from the International Energy Agency (IEA).

Global electricity demand from datacentres will more than double by 2030, according to the report. AI will be the main driver of that increase, with demand from dedicated AI datacentres alone forecast to more than quadruple.

One datacentre today consumes as much electricity as 100,000 households, but some of those currently under construction will require 20 times more.

But fears that the rapid adoption of AI will destroy hopes of tackling the climate crisis have been “overstated”, according to the report, which was published on Thursday. That is because harnessing AI to make energy use and other activities more efficient could result in savings that reduce greenhouse gas emissions overall.

Fatih Birol, the executive director of the IEA, said: “With the rise of AI, the energy sector is at the forefront of one of the most important technological revolutions of our time. AI is a tool, potentially an incredibly powerful one, but it is up to us – our societies, governments and companies – how we use it.”

Using AI could make it easier to design electricity grids to take more renewable energy. Most grids were designed for centralised fossil fuel power stations that produce reliable levels of electricity, some of which can be turned off and on relatively quickly. They have to be redesigned to balance demand when more of the supply comes from intermittent and sometimes unpredictable sources, such as wind and solar power.

Finding efficiencies within energy systems, and in industrial processes, could also become easier with AI. At present, huge opportunities to increase efficiency are missed, because it is harder for companies to change their processes than to carry on with wasteful practices.

AI could also assist with new technologies such as driverless vehicles or detecting threats to vital infrastructure. The technology could also be used to plan public transport to optimise for people’s journeys, or to design cities or traffic systems. Mining companies could use AI to discover and exploit reserves of critical minerals, which are crucial to modern renewable energy components such as solar panels, wind turbines and electric vehicles.

These uses could offset some of the massive demands that AI will place on the world’s energy systems. But that is likely to require greater direction from governments, the IEA report found. Left alone, the rapid growth of AI could prove a severe problem for energy systems and the environment.

AI has the potential to reverse all the gains made in recent years in advanced economies to reduce their energy use, mainly through efficiencies. The rapid increase in AI also means companies will seek the most readily available energy – which could come from gas plants, which were on their way out in many developed countries. In the US, the demand could even be met by coal-fired power stations being given a new lease on life, aided by Donald Trump’s enthusiasm for them.

Done badly, AI could also suck water from some of the world’s driest areas, an investigation by the Guardian revealed, as many AI datacentres use vast quantities of fresh water for cooling their computers.

Claude Turmes, a former Green MEP and energy minister for Luxembourg, said the disadvantages of AI were more likely to materialise than the optimistic projections of the IEA, and governments needed much more help to avoid the pitfalls.

He accused the IEA of painting too rosy a picture and failing to spell out harsh truths to policymakers. He said: “Instead of making practical recommendations to governments on how to regulate and thus minimise the huge negative impact of AI and new mega datacentres on the energy system, the IEA and its [chief] Fatih Birol are making a welcome gift to the new Trump administration and the tech companies which sponsored this new US government.”

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