Artificial intelligence (AI) is rapidly changing how industries operate, and it could also help fight climate change. A major study published in npj Climate Action finds that AI could cut global carbon emissions by up to 5.4 billion tonnes per year by 2035. That’s more than the total annual emissions of the United States.
The study is led by researchers from the London School of Economics and Systemiq. The report entitled “Green and intelligent: the role of AI in the climate transition” shows that applying AI to three key sectors—food, electricity, and mobility—can unlock enormous environmental benefits.
AI’s strength lies in its ability to process large datasets, identify patterns, and optimize systems in real time. When used strategically, this can translate into greater efficiency, lower energy use, and less waste. These improvements are essential to reduce greenhouse gas emissions and slow climate change.
A Sector-by-Sector Breakdown: Where AI Delivers the Most Cuts
The study highlights three areas where AI can drive the biggest reductions in carbon dioxide equivalent (CO₂e) emissions:
- Food: 0.9–1.6 billion tonnes CO₂e per year (up to 3.0 GtCO₂e in a highly ambitious scenario)
- Energy (Electricity): Up to 1.8 billion tonnes CO₂e per year
- Mobility (Transport): 0.5–0.6 billion tonnes CO₂e per year
These figures are significant. Together, they represent 8% to 10% of total global greenhouse gas emissions. That’s a substantial contribution to international efforts like the Paris Agreement, which aims to limit global warming to well below 2°C.
In the food and agriculture sector, AI can improve productivity while reducing environmental harm. Smart sensors and machine learning tools help farmers use just the right amount of water, fertilizer, and pesticides.
AI also enables precision farming, reducing waste and cutting emissions from overuse of chemicals. It can predict crop yields and improve food distribution. This helps cut spoilage and lowers emissions from storage and transport.
AI helps the clean energy transition in electricity generation. It manages supply and demand more efficiently. Moreover, AI algorithms can predict electricity use. They also enhance energy storage and optimize the integration of solar and wind power.
Additionally, AI helps stabilize power grids and boosts low-carbon energy use. This cuts down the need for dirty backup systems that run on coal or gas.
For mobility and transport, AI improves logistics, reduces fuel use, and supports the development of cleaner vehicles. Fleet managers use AI to plan efficient routes, avoid traffic, and reduce idle times. AI is key to making self-driving cars. These vehicles could boost road safety and cut emissions even more.
The chart below shows the projected global emissions by 2035, with AI adoption differing from business-as-usual and ambitious reduction scenarios for the three sectors identified.
AI Carbon Reductions in Other Sectors
AI is also critical in industries like cement and steel, where emissions are hard to abate. Machine learning helps monitor production processes and reduce energy waste. AI also enables real-time emissions tracking and reporting, helping companies stay accountable to their climate goals.
A recent McKinsey report shows that AI technologies can help businesses lower CO₂ emissions by up to 10%. They can also reduce energy costs by 10–20%. Additionally, buildings could save 20% on energy, while transportation systems might save 15%.
Complementing this, the International Energy Agency (IEA) estimates that adopting existing AI applications across end-use sectors like energy, industry, transport, and buildings could reduce emissions by about 1.4 gigatons of CO₂ annually.
Together, these findings underscore AI’s significant role in accelerating decarbonization across multiple sectors. And the good news? These AI applications already exist and are being tested or deployed by companies around the world. What’s needed now is rapid scaling.
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The Role of Policy and Industry Action
The study authors say AI’s benefits will only happen with strong guidance from policymakers and investors. Without supportive rules and incentives, AI might raise emissions. It could increase demand for power-hungry data centers. Also, it may automate processes that lead to more production and consumption.
To avoid these risks, the researchers call for:
- Public and private investment in climate-focused AI tools
- Open access to high-quality environmental datasets
- Standards and guardrails to guide responsible use
They also warn against “AI rebound effects,” where efficiency gains are offset by increased consumption. For example, making vehicles more fuel-efficient might encourage people to drive more. That’s why careful planning and strong governance are essential.
Another key recommendation: include developing countries in the AI transition. These regions often face the greatest climate risks but have limited access to technology. Thus, international partnerships and funding will be needed to ensure AI’s climate benefits are shared globally.
AI as a Climate Enabler, Not Just a Tool
AI can also strengthen other climate solutions. For example:
- Carbon removal. AI helps track carbon storage in forests and soils, improving the quality of carbon credits and offset programs.
- Resilience planning. AI models assist cities in getting ready for floods, heat waves, and other climate effects. They do this by simulating different scenarios and testing response plans.
- Energy optimization. AI manages heating, cooling, and lighting in buildings. It cuts energy waste while keeping comfort high.
These applications make climate solutions smarter, cheaper, and faster. AI doesn’t just reduce emissions—it helps manage the clean energy transition more effectively.
Governments are starting to notice. The European Union and Canada have launched initiatives to support green AI. Companies like Google, Microsoft, and Amazon are also building AI tools for climate forecasting, carbon tracking, and energy management.
Tech vs. Time: Can AI Help Us Beat the Climate Clock?
The new study offers compelling evidence that AI could play a leading role in slashing global carbon emissions. The estimated 3.2 to 5.4 billion tonnes of CO₂e reductions by 2035 are not just theoretical; they’re within reach if the right steps are taken.
These findings come at a time when many countries are off track in meeting their 2030 and 2050 climate goals. AI may help close that gap by offering fast, reliable, and affordable emissions cuts in important sectors.
Private companies, too, are under pressure to deliver on net-zero commitments. For them, AI can provide tools to track emissions, meet regulatory standards, and optimize energy use. Investors are also watching closely, with many ESG (environmental, social, governance) funds now looking for AI-powered climate solutions.
The bottom line? AI can become one of the world’s most powerful climate allies. But its impact depends on how it’s used, who controls it, and whether its benefits are shared widely. By focusing on climate-smart applications in food, electricity, and transport, AI can help build a cleaner, more resilient future.
