Researchers have conducted the first comprehensive analysis of artificial intelligence’s climate impact across the entire power sector, revealing a concerning net increase in carbon emissions despite AI’s potential benefits for renewable energy.
The study modeled 64 different scenarios examining AI’s technical capacity to enhance both clean power generation and fossil fuel production. Across these scenarios, researchers found that yearly carbon pollution increased by between 0.47 and 1.8 gigatonnes—representing approximately 1 to 5 percent of annual energy sector emissions. The analysis diverges from previous research by accounting for AI’s productivity gains in coal, oil, and gas extraction, which earlier studies had largely overlooked while focusing on direct renewable energy benefits.
A critical finding indicates that net emissions would only decrease in scenarios where artificial intelligence does not boost productivity in fossil fuel operations. The researchers determined that if both clean and dirty energy sectors adopted AI at equivalent rates, renewable productivity gains would need to outpace fossil fuel productivity improvements by a factor of at least four just to achieve emissions neutrality. Industry data suggests this outcome remains unlikely, as fossil fuel companies are already deploying AI at scale across multiple operations, while renewable applications remain largely experimental or pilot-stage.
The fossil fuel industry has demonstrated significant enthusiasm for AI deployment. The International Energy Agency projects that AI could increase technically recoverable oil and gas reserves by 5 percent and reduce deepwater offshore project costs by 10 percent. Major oil and gas operators including Saudi Aramco and Equinor have publicized substantial productivity increases and new discoveries attributed to AI implementation. Research firm Rystad Energy estimated in May that AI-driven efficiencies could generate approximately $500 billion in cumulative value for fossil fuel companies between 2026 and 2030.
The study’s findings suggest that AI’s impact on fossil fuel productivity generates emissions at least three times greater than current estimates for energy-intensive AI datacenters alone. Researchers emphasized their results represent directional findings rather than precise forecasts, though the pattern remained consistent across all tested scenarios and sensitivity analyses.
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