AI Can Substantially Reduce Global Carbon Emissions

AI Can Substantially Reduce Global Carbon Emissions

As the global climate crisis intensifies, industries are under increasing pressure to find solutions that align economic growth with environmental responsibility. Amid this challenge, AI is emerging not just as a tool of convenience but as a strategic asset in achieving sustainability goals.

A recent study conducted by the London School of Economics and Systemiq highlights the potential of artificial intelligence (AI) to significantly mitigate global carbon emissions. According to the research, AI applications in three crucial industries can annually cut carbon emissions by 3.2 to 5.4 billion tonnes, all while maintaining modern living standards.

AI technology, recognised for its versatility and efficiency, can be employed in various sectors to optimise processes and reduce waste.

In transportation, for example, AI can enhance traffic management and improve logistics, resulting in lower fuel consumption and reduced emissions.

In energy, AI helps in predictive maintenance and optimising energy usage. Meanwhile, in manufacturing, AI can streamline production processes, minimise defects, and reduce overall resource consumption.

These advancements demonstrate that AI not only has the potential to foster technological innovation but also to support sustainable practices.

By integrating AI solutions, industries can make substantial progress towards reducing their carbon footprint.

The long-term impact, however, will depend on scaling these technologies responsibly and ensuring equitable access across regions and sectors.

Policymakers and industry leaders alike must now focus on creating regulatory frameworks and investment incentives that align AI development with climate targets.

As both a climate tool and a catalyst for operational transformation, AI could become one of the most powerful levers in steering the global economy towards a low-carbon future.

Key Findings from the Report

  • AI’s Emissions Reduction Potential:
    • The study, published in npj Climate Action and summarised by LSE and Systemiq, finds that AI applications in the power, transport, and food sectors could reduce global greenhouse gas emissions by 3.2 to 5.4 billion tonnes of CO₂ equivalent annually by 2035 (LSE Grantham Institute Press Release | Systemiq Summary | npj Climate Action, June 2025).
    • These three sectors together account for about half of all global emissions.
  • Sector-Specific Impacts:
    • Power: AI can improve grid management and forecasting, potentially boosting the output of wind and solar installations by up to 20%.
    • Transport: AI can optimise logistics, traffic management, and encourage shifts to lower-emission transport modes.
    • Food: AI can accelerate the adoption of alternative proteins, reduce food waste, and optimise supply chains.
  • AI’s Net Impact:
    • The emissions savings from these AI applications far outweigh the carbon footprint of AI itself, including data centres and supporting infrastructure (AI News).
  • Five Core Functions of AI for Climate:
    1. Improving complex systems (e.g., energy grids)
    2. Speeding up innovation (e.g., new materials for batteries)
    3. Encouraging behavioural shifts (e.g., sustainable diets)
    4. Shaping better policies
    5. Strengthening resilience and adaptation (e.g., disaster prediction)
  • Policy and Investment Needs:
    • The report stresses that realising this potential requires targeted public investment, shared data, and equitable access to AI capabilities.
    • Policymakers must create regulatory frameworks and incentives that align AI development with climate targets.

References

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