IEA: AI holds potential to reduce emissions worth three times its own footprint

A new report by the International Energy Agency suggests that, if widely adopted across energy-intensive industries, artificial intelligence (AI) could drive emissions reductions three times larger than what AI’s own electricity demand is expected to cause.

The study, drawing on new datasets and extensive consultation with policymakers, the tech sector, the energy industry and international experts, suggests that, under the right conditions, AI’s emissions benefits would largely outweigh its impacts.

“The adoption of existing AI applications in end-use sectors could lead to 1,400 million tonnes of CO2 emissions reductions in 2035 in the Widespread Adoption Case. This does not include any breakthrough discoveries that may emerge thanks to AI in the next decade. These potential emissions reductions, if realised, would be three times larger than the total data centre emissions in the Lift-off Case, and four times larger than those in the Base Case,” the IEA says in the report.  

However, the Agency also warns that “there is currently no momentum that could ensure the widespread adoption of these AI applications”, with barriers to adoption including limited access to data, lack of digital infrastructure and skills, regulatory and security restrictions and social or cultural obstacles.

Even after 2035, AI’s impact on emissions could remain “marginal” if these obstacles are not overcome.

AI-driven electricity demand set to quadruple over the next five years

At the same time, the report reveals the scale of the energy impact of AI. Demand from data centres worldwide is projected to more than double over the next five years, to around 945 terawatt-hours (TWh) – more than the entire electricity consumption of Japan. 

AI will be the largest driver of this increase, with electricity demand from AI-optimised data centres set to more than quadruple within the same timeframe.

This will particularly be felt in developed economies: in the US, power consumption by data centres is on course to account for almost half of the growth in electricity demand between now and 2030. This means that by the end of the decade, the US could consume more electricity for processing data than to manufacture all energy-intensive goods combined – including aluminium, steel, cement and chemicals. 

Across developed economies, data centres are projected to drive more than 20% of the growth in electricity demand between now and 2030. This highlights the need to develop a broad range of low-carbon electricity sources to meet AI’s rising power demands.

Energy security and critical minerals

The report also warns that AI could intensify some energy security concerns, while also helping to address others. For example, cyberattacks on energy utilities have tripled in the past four years and become more sophisticated because of AI – yet AI is becoming a critical tool for energy companies to defend against such attacks. 

“With the rise of AI, the energy sector is at the forefront of one of the most important technological revolutions of our time,” said IEA Executive Director Fatih Birol. “AI is a tool, potentially an incredibly powerful one, but it is up to us – our societies, governments and companies – how we use it. The IEA will continue to provide the data, analysis and forums for dialogue to help policy makers and other stakeholders navigate the path ahead as the energy sector shapes the future of AI – and AI shapes the future of energy.”