Study: AI could actually cut global emissions by 5.4B tons annually by 2035

New research suggests artificial intelligence could cut global climate pollution by up to 5.4 billion metric tons annually by 2035—far exceeding the emissions created by AI’s own energy-hungry data centers. The findings from the Grantham Research Institute challenge growing concerns about AI’s environmental impact, showing that strategic deployment across transportation, energy, and food systems could deliver net climate benefits equivalent to eliminating all of the European Union’s current emissions.

The big picture: AI’s climate potential hinges on governments channeling the technology toward high-impact applications rather than letting market forces alone dictate its development.

• The study identifies five key areas where AI can reduce emissions: consumer behavior modification, energy management optimization, technology innovation acceleration, renewable energy integration, and sustainable food production.
• Strategic government intervention is essential to ensure AI development prioritizes climate solutions over purely commercial applications.

Key details: AI applications could transform three critical sectors responsible for massive global emissions.

• Energy management: AI can better forecast renewable energy supply and demand fluctuations, helping integrate more solar and wind power while reducing reliance on polluting backup sources.
• Food production: AI can identify new protein alternatives to replace high-emission meat and dairy industries.
• Transportation: The technology can lower electric vehicle costs through battery improvements and encourage shared transport adoption.

The energy challenge: Data centers supporting AI will significantly increase global electricity consumption, but the climate math still works in AI’s favor.

• The International Energy Agency projects data centers will consume twice as much electricity by 2030 compared to current levels.
• BloombergNEF, a research firm, estimates fossil fuels will provide most new power for data centers over the next decade.
• However, AI’s direct emissions are projected at just 0.4 billion to 1.6 billion metric tons of CO2 equivalent over the next decade—far below potential savings.

What they’re saying: Researchers emphasize that realizing AI’s climate potential requires deliberate policy choices.

• “The key will be to channel practical AI applications towards key impact areas to accelerate the market adoption rate and efficiency of low-carbon solutions,” the study noted.
• “Power grids are at the heart of the entire economy, so improving their efficiency reduces emissions across multiple sectors,” explained Roberta Pierfederici, the study’s author and a policy fellow at the Grantham Research Institute.

Important context: The research comes as President Trump prioritizes AI expansion to outcompete China, while arguing that winning the AI race justifies expanding fossil fuel production.

• The potential 3.2 billion to 5.4 billion metric ton reduction represents a significant portion of global emissions—for comparison, the U.S. released 6.2 billion metric tons of climate pollution in 2023.
• While substantial, these cuts alone wouldn’t meet the 1.5-degree Celsius warming target but could meaningfully slow climate change.

Study limitations: The rapidly evolving AI landscape introduces uncertainty in both directions.

• Researchers may have underestimated AI’s emission reduction potential by focusing on only three sectors and current applications.
• The analysis didn’t account for potential “rebound effects,” where AI-driven efficiency gains could lead to increased consumption elsewhere, potentially driving up emissions.