Major global powers are now navigating the intersection between the growing urgency of climate change and the rapid evolution of artificial intelligence. As AI becomes a key driver of economic innovation and public policy, an important question arises: can it be used meaningfully to advance climate goals, and if so, how do we ensure it’s applied wisely? From helping manage energy systems to monitoring environmental changes, AI is already playing a role. Yet its expansion brings new concerns, including high energy consumption, unequal access to data, and the risk of climate efforts being misrepresented. As nations work toward decarbonization, these complexities are becoming harder to ignore.

The Good and Bad of Using AI for Climate Action

AI is becoming a powerful tool in the fight against climate change. It’s being used in areas like smart energy use, tracking emissions, farming, water safety, and disaster warnings. These tools can help cut emissions, make systems more efficient, and help communities adapt. For instance, AI can help manage renewable energy by predicting demand and cutting waste, and it can help businesses measure their carbon footprints more easily and affordably. But there are also risks. Training and running large AI models uses a lot of electricity and creates significant emissions. If AI continues to grow without the tech industry switching to clean energy fast enough, it could actually make the climate crisis worse. 

Carbon Emissions

Running and training AI systems create significant carbon emissions. For example, training just one large model like BLOOM produced at least 25 tonnes of CO₂, and up to 50 tonnes over its full life cycle, which is about the same as dozens of transatlantic flights. AI is also using more electricity. By 2025, AI could take up as much as 20% of all data center energy globally, using around 82 terawatt-hours. This is similar to what Switzerland uses in a year.  Experts warn that if we don’t regulate AI development carefully, its environmental impact could cancel out its climate benefits. 

Inequity in Climate Data and Access

AI tools need strong data like satellite images, smart-grid info and city sensors to work well. But many lower-income regions don’t have this kind of data system in place, which makes it harder for them to use AI for climate solutions. Studies also show that wealthier countries have more consistent and aligned climate plans and progress reports, while poorer nations often have missing or weaker data. This creates an unfair advantage in global climate decisions. 

Using Policy and Data to Tackle Climate Change 

The future of climate governance will rely on a few important shifts happening at once. More money is going into digital and AI tools, especially in developing countries that still lack the resources they need. There’s also a push to standardize how climate data is collected and shared, so AI can work with better and more complete information. At the same time, experts are calling for clearer rules around AI’s energy use and how to keep its environmental impact low. Cooperation between countries will be key to set fair standards, share technology, and make sure poorer nations aren’t left behind. AI can’t replace strong leadership or community involvement, but if used wisely, it could help speed up the search for solutions we desperately need.

The Future is Ours to Shape

As the world pushes to meet climate goals, AI is both a powerful tool and a potential risk. The way we develop and govern AI today will shape whether it helps close climate gaps or makes them worse. For both governments and businesses, AI will only support real climate progress if we pair innovation with responsibility. That means being honest about its limits, reducing its own carbon footprint, and making sure its benefits are shared fairly. Without smart policies and strong accountability, AI could end up reinforcing inequality or delaying the transition to clean energy. AI is a force that must be guided with care, fairness, and foresight.