Modelling finds AI-driven productivity gains in coal, oil and gas enable more emissions than applications in renewables avoid
AI-driven productivity gains enable more planet-heating pollution from fossil fuels than they avoid from renewables, a study has found.
Researchers modelled the technical potential for AI to boost clean power generation along with projections for how it can help produce coal, oil and gas. Across 64 scenarios, they found net yearly carbon pollution rose by 0.47-1.8 gigatonnes, or about 1-5% of the energy sector’s annual emissions.
The study is the first to quantify the climate impact of AI across the full power sector. Previous research has explored its indirect climate benefits – such as reducing renewable downtime and optimising electricity grids – while ignoring the extra pollution from increasing productivity in drilling oil wells and extracting gas.
“What most studies have done so far … is compare the datacentre energy use with the emissions savings AI has,” said Lynn Kaack, an assistant professor of computer science and public policy at the Hertie School who provided feedback on a draft of the research. “They completely omit this picture of AI causing increases in emissions.”
The researchers found net emissions only fell in scenarios where AI did not increase productivity in the fossil fuel sector. If clean and dirty energy facilities were to adopt AI at similar rates, they found, the productivity gains for renewables would have to outpace those for fossil fuels by at least four times for emissions to break even.
Holly Alpine, a co-author of the study and a former Microsoft employee who left to co-found the Enabled Emissions campaign group, said the research team used a conservative assumption that AI adoption would happen at the same rate for fossil fuels and renewables.
“Fossil fuel applications are already happening at scale today – real contracts, real deployment, with evidence from industry operators and financial analysts,” she said. “Renewables applications are still largely at the pilot or academic-study stage – more speculative, more dependent on deployment barriers like permitting and interconnection getting resolved.”
The International Energy Agency estimates that AI could boost technically recoverable oil and gas reserves by 5% and cut the cost of deepwater offshore projects by 10%. Oil and gas executives have been enthusiastic about the extra fuel that AI has allowed them to find, and celebrated its emerging impact as “the next fracking boom”.
Saudi Aramco said last year that it had embedded AI “in everything”, increasing productivity and the number of wells, while earlier this summer Equinor attributed 27 discoveries on the Norwegian continental shelf to new seismic technologies and AI. The findings include the Lofn and Langermann oil wells, which the company said was the largest discovery it operated in 2025. “AI was key, from automated data interpretation to efficient well planning,” it said in a video at its capital markets day in June.
Rystad Energy, an independent research and energy intelligence company based in Oslo, estimated in May that digitalisation and AI would create close to $500bn (£370bn) in cumulative value for fossil fuel exploration and production companies between 2026 and 2030 – the result of more efficient operations, increased production, and shorter development timelines. “The returns are already visible in the industry,” its analysts wrote, citing hundreds of millions of dollars in reported AI-related savings from Equinor and Abu Dhabi’s Adnoc.
Climate scientists and energy experts have been troubled by the rapid construction of increasingly large and energy-hungry AI datacentres, which are typically powered by burning fossil gas. The researchers did not factor datacentre energy demand into their calculations but found AI enables productivity gains in the fossil fuel sector that result in emissions at least three times current estimates for datacentres.
They cautioned that the results were a “directional and structural finding, not a precise forecast”, though the broad relationship held true across every scenario and sensitivity test they ran.
Ketan Joshi, an independent climate analyst who was not involved in the study, said the AI sector was “fundamentally hungry for fossil fuels” and that the impacts went well beyond data centres driving fossil fuel use.
“Even within some parts of the climate movement, there is still a denial that an unchecked tech industry will inherently boost fossil fuels,” he said. “Simply asking companies to throw a few scraps of cash at renewable projects is not enough to ensure the industry operates safely.”
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