AI in Oil and Gas Could Add More Emissions Than It Saves

Artificial intelligence is transforming the oil and gas industry in ways that could significantly increase global carbon emissions, according to new peer-reviewed research that challenges the conventional focus on data center energy consumption.

Why it matters

While much attention has centered on the electricity AI systems consume, this research suggests the technology's larger climate impact may come from making fossil fuel extraction more efficient and profitable — a dynamic largely absent from current policy discussions about AI governance.

The research findings

A study published in a Nature journal estimates that AI-driven improvements in oil and gas production could add emissions equivalent to 1% to 5% of the global energy sector's 2024 output. According to the researchers, these emissions would be roughly three to 13 times larger than current data center emissions as estimated by the International Energy Agency.

The study was led by Holly Alpine and Will Alpine, former Microsoft employees who founded the nonprofit Enabled Emissions Campaign in 2024, working with researchers from Purdue University and an independent researcher. Details were first reported by Axios.

"Most assessments of AI's climate impact are framed as a tradeoff between data center energy use and the emissions AI might help avoid through renewables and efficiency gains," Holly Alpine said. "What's missing from that calculation entirely is the other side of the same ledger: the emissions enabled from using AI to make fossil fuel production cheaper and more profitable."

The researchers used an economic model to simulate how AI-driven productivity gains propagate through energy markets. Across 64 modeled scenarios, emissions declined only when AI provided zero productivity gains to fossil fuel operations.

Industry adoption accelerating

Major oil producers including Chevron, ExxonMobil, ADNOC and Aramco are already deploying AI to identify drilling prospects and improve recovery rates from existing fields. Oilfield service companies SLB, Halliburton and Baker Hughes are using the technology to guide drilling operations and optimize well placement.

Analysts from Goldman Sachs to Wood Mackenzie project that AI will lower production costs and increase economically recoverable reserves.

The American Petroleum Institute disputed the premise that increased energy production conflicts with emissions reduction. "The U.S. oil and natural gas industry is continuing to produce more energy while reducing emissions by investing in better technology, implementing stronger operational practices and supporting science-based policy," spokesperson Andrea Woods said.

The modeling limitations

The study does not attempt to quantify AI's potential to accelerate breakthrough clean technologies such as fusion energy or long-duration storage. "There is a lot of AI dreaming out there," said Michael Lazarus, senior scientist emeritus at Stockholm Environment Institute who advised the authors. "I don't know how one would anticipate that and model it."

Brian Janous, who previously worked with Holly Alpine at Microsoft and now runs data center developer Cloverleaf Infrastructure, suggested the competitive dynamics may favor clean energy regardless. "I think cleantech is going to win anyway, so let's just focus on how we unlock clean energy resources with AI," he said.

The study's authors are calling for greater transparency about AI's effects across all sectors to enable informed governance decisions.

Axios first reported these findings.