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CommentaryAI

AI could accelerate progress toward the world’s climate goals. Here’s how

By
Kate Brandt
Kate Brandt
and
Rich Lesser
Rich Lesser
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By
Kate Brandt
Kate Brandt
and
Rich Lesser
Rich Lesser
Down Arrow Button Icon
December 18, 2023, 10:44 AM ET
In California, artificial intelligence is being used to process wildfire camera data and provide automated wildfire notifications.
In California, artificial intelligence is being used to process wildfire camera data and provide automated wildfire notifications.Jason Henry - Bloomberg - Getty Images

The world must dramatically reduce greenhouse gas emissions by 2030 to meet Paris Agreement goals. Yet based on current trajectories, emissions are set to rise by 10% over the next eight years. This will only accelerate widespread droughts, flooding, extreme heat, and other devastating impacts across the globe.

Against this challenging backdrop, it is clear that acceleration is needed across all fronts of climate action. One of those opportunities lies in artificial intelligence (AI). Research shows that by scaling currently proven applications and technology, AI could mitigate 5 to 10% of global greenhouse gas emissions by 2030–the equivalent of the total annual emissions of the European Union. For the first time, AI was highlighted at COP28 as one of the key potential solutions to tackle climate change, with the United Nations Framework Convention on Climate Change (UNFCCC) announcing the AI Innovation Grand Challenge at the conference to identify and support the development of AI-powered solutions for climate action in developing countries.

Reversing the emissions trajectory will take everyone involved–government officials, business leaders, and technologists–all rowing the boat in the same direction. Policymakers have a central role to play, with three critical priority areas that will allow AI to contribute to its full potential.

First, policies must enable AI innovation and adoption for climate-positive applications. Data sharing frameworks, investment in research, affordable technology access, and education initiatives are needed to drive development and deployment. Government has a key role to play as an end-user. In the absence of clear community, national, or sector-specific objectives for climate action, AI-driven innovation could go off in disjointed directions. Resource allocation would be inefficient. Establishing priority innovation domains where AI could most immediately and effectively advance climate action–such as leveraging AI for flood-resilient farming, climate change adaptation, and accelerating the energy transition–can unlock resources and focus minds. 

Second, policymakers should accelerate AI’s climate impact by prioritizing high-potential use cases and embedding efficiency and optimization requirements into industrial regulation. Existing processes and legacy infrastructure in high-emission sectors like aviation, manufacturing, electricity production, and construction, could be more immediately optimized with AI, not just with wholesale reconstruction, which could be costly and take too much time. Long-term transformative investments still need to be made, but more immediate impact should be encouraged.

Third, policymakers can help ensure that the computing resources needed for AI advances are powered by carbon-free energy–for example, through improvements to electricity grids like better load management which AI can enable. 

AI can be critical in our collective effort to tackle climate change. AI is already driving progress by helping individuals get better and more actionable information, businesses optimize their operations, and governments and other organizations improve prediction and forecasting. 

Germany’s Energy Efficiency Act includes specific regulations requiring data centers to purchase renewable energy and mandates the reuse of the heat they generate.

Singapore is using AI to predict floods and test flood-resilient infrastructure. The city of Lisbon is utilizing AI to map its current inventory of solar panels and assess expansion potential. The data collected is then used to develop forecasts for renewable energy supply, which in turn informs building codes and incentive budgets. The Philippines is advocating using AI to tackle climate change adaptation challenges and disaster risk reduction.

Policymakers globally have been focused on promoting the responsible development of AI–which is critical. But they must also pursue a policy agenda to harness AI’s potential to solve big challenges like climate change. Enabling this technology through smart policy decisions may prove one of the most impactful climate actions we can take today–and would provide a vital down payment on goals to significantly reduce emissions during this decade.

Kate Brandt is the chief sustainability officer at Google. She previously served in the White House as the US’s first Federal Chief Sustainability Office, Senior Advisor at the Department of Energy, and Energy Advisor to the Secretary of the Navy.

Rich Lesser is the global chair at Boston Consulting Group (BCG). He also serves as chief advisor to the World Economic Forum Alliance of CEO Climate Leaders.

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The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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