By Robert Bradley Jr.
“Absent [climate] policy steering [intervention], AI’s modeled effects increase the carbon intensity of the global economy and reinforce fossil fuel incumbency—outcomes that current analytical and governance frameworks do not fully capture.” (Nature Portfolio, below)
Age-old fears of declining fossil fuel supply and falling demand have, once again, been upended by the engines of progress. The anti-CO2 crusade, futile and wasteful, has been set back again. Tsvetana Paraskova’s “AI Could Make Big Oil Even Bigger” (OilPrice.com: August 18, 2026) gives the supply-side story:
AI could strengthen fossil fuels, with oil and gas productivity gains potentially outweighing emissions savings from renewables.
- AI could create nearly $500 billion in value for E&P companies by 2030 through lower costs and higher production.
- Exxon and Chevron are already deploying AI in exploration, potentially uncovering new drilling opportunities and accelerating development.
“Arguably, a fundamental change in the energy system may not come from surging power demand,” she writes, “but from the efficiencies and productivity gains AI will help energy companies achieve, according to a new paper published in the journal npj Climate Action by co-authors, some of whom have worked for Microsoft and its sustainability initiatives.” (“npj” stands for “Nature Partner Journal.”)
The abstract of “AI-driven Productivity Gains Enable More CO₂ Emissions than They Avoid in a Global Energy–economy Model” (Nature Portfolio: August 5, 2026) follows:
The net climate impacts of artificial intelligence (AI) depend largely on how its applications propagate through competing energy pathways. Predominant analyses examine the relationship between datacenter energy demand, renewables optimization, and demand-side efficiencies, but insufficiently address how AI also reshapes fossil fuel supply economics.
We instead model AI as a bidirectional productivity amplifier in a global computable general equilibrium model, quantifying both enabled emissions from fossil fuel productivity gains and avoided emissions from renewables productivity gains. Under parallel adoption scenarios, net annual CO₂ emissions increase by 0.47–1.8 gigatonnes (1.2–4.8% of 2024 global energy-related CO₂ emissions).
Enabled emissions exceed avoided emissions whenever fossil-sector gains are nonzero; net emissions reductions require renewables gains 4–5× greater than fossil fuel gains. Absent policy steering, AI’s modeled effects increase the carbon intensity of the global economy and reinforce fossil fuel incumbency—outcomes that current analytical and governance frameworks do not fully capture.
