Artificial intelligence can play a powerful role in supporting climate action and low-carbon transition while boosting sustainable and inclusive economic growth, a new paper led by researchers at the London School of Economics says. The paper was published this week in the journal Nature.

The authors found four major ways in which they believe AI can be utilized to support climate actions:

• The application of AI models to better design and implement policies for climate action, by generating insights and predictions around complex climate policy scenarios or monitoring the effectiveness of policy implementation.
• Supporting long-term resilience and adaptation through its ability to create large-scale simulations tracking how ecosystems might evolve.
• Improving early warning systems for extreme weather events, such as floods and wildfires, enabling governments and communities to take proactive measures to mitigate damage, saving lives and significant costs.
• Using AI to better predict investment risks and returns, improving financial decisions where information is scarcer, particularly in emerging markets where perceived risk is high, often due to limited and asymmetric information.

The authors also estimate the potential for greenhouse gas emission reductions through AI applications in three key sectors – power, food and mobility – which collectively contribute nearly half of global emissions. They find that advancements in AI in power, transport and food consumption could reduce global emissions of greenhouse gases by 3.2 to 5.4 billion tons of carbon-dioxide-equivalent annually by 2035.

“While AI can contribute to emissions increase through data centers’ energy consumption, our estimates show that the emissions reduction potential from AI applications in just (those) three sectors alone would more than offset the total AI’s emissions increase in all economic activities, making a strong case for using AI for resolving the climate threat,” the authors wrote.

In the power sector, AI can improve the efficiency of renewable energy systems by optimizing grid management and increasing the load factor of solar photovoltaics and wind by as much as 20%. AI could also improve the adoption rates of alternative non-animal food proteins by as much as 27–50% in a “highly ambitious” AI scenario.

“These sectors are highly interconnected, hence accelerating the adoption and efficiency of low-carbon solutions will no doubt trigger technological tipping points elsewhere, resulting in cascading effects across the economy,” they wrote.

The authors warned that letting markets alone determine the applications and governance of AI could prove to be risky. Governments have a critical role in ensuring that AI is deployed effectively to accelerate the transition equitably and sustainably, the paper concludes.

“By fostering innovation, directing investment, and promoting international cooperation, governments can ensure that AI delivers both environmental and economic benefits, paving the way for a sustainable future,” they said.

The study authors include Nicholas Stern, Mattia Romani and Roberta Pierfederici from the London School of Economics’ Grantham Research Institute and Mattia Romani, Manuel Braun, Daniel Barraclough, Shajeeshan Lingeswaran, Elizabeth Weirich-Benet and Niklas Niemann from London-based Systemiq, a company that seeks to bring speed and scale to transforming five systems that shape how we live and work: energy, nature and food, materials, urban areas and finance.

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