How AI can help fight climate change: 5 powerful use
AI is rarely out of the headlines. Depending on what you read, it’s either a miracle tech destined to reshape humanity, or a threat to jobs, democracy and civilisation itself.
The climate implications tend to be buried down the page - the water needed to cool vast data centres, the electricity required to train the LLMs (large language models), and the uncomfortable fact that one single AI search can consume ten times more energy than a standard Google query.
It’s true: AI is no carbon-neutral saviour. If misdirected, it risks becoming yet another accelerant of overconsumption. But to dismiss it outright is to miss the bigger picture. Like all tools, its impact depends on how it’s wielded. The same algorithms that generate infographics or write holiday itineraries could, in the right hands, help us balance renewable power grids, expose illegal deforestation, or design the next generation of carbon-capture materials.
AI is here to stay; there’s no doubt about that. The question is whether we can channel its enormous capabilities towards the most urgent challenge of our time: the climate crisis.
Here are five ways it’s already beginning to do so.
1. Balancing the energy transition
Renewable energy is often criticised for its unpredictability. Solar panels sit idle at night; wind farms slow to a crawl on still days. The challenge has always been how to capture, store and distribute that energy efficiently. AI offers a step change.
“AI can be an asset for climate and energy - but only if its development is guided by actual climate needs and planetary limits.”
By combining real-time weather forecasts, grid data and historical patterns, machine-learning models can predict when renewable generation will spike, and when demand will outstrip supply. Denmark’s national grid, for example, already uses AI systems to help balance fluctuating wind power, cutting waste and reducing reliance on fossil-fuel backup. It’s the kind of optimisation that, scaled globally, could make renewables not only cleaner, but more dependable than coal or gas.
🔎 READ: MIT Technology Review’s article on AI’s energy impact is still small - but how we handle it is huge.
2. Watching the world in real time
Until recently, emissions data was patchy, delayed and - crucially - self-reported. AI has changed that. Satellites equipped with computer vision can now detect methane leaks from oil and gas fields, measure deforestation metre by metre, and even monitor changes in ocean temperature with startling precision.
Companies like GHGSat already provide satellite imagery that pinpoints methane plumes from space, offering regulators and campaigners irrefutable evidence.
In an age when climate targets too often dissolve into rhetoric, the power of independent, real-time monitoring cannot be overstated. It makes accountability immediate - and excuses harder to maintain.
🔎 READ: Clean Technica’s article, MethaneSAT’s Silence Won’t Save Methane Emitters From Scrutiny.
3. Making cities breathe easier
Cities are where the climate crisis is most visible - and most solvable. They produce more than 70% of global emissions, but are also the testing ground for new technologies. AI is already weaving itself into the urban fabric.
In the US, AI-controlled traffic lights have been shown to reduce idling time by over a fifth, cutting both congestion and emissions. Smart building systems adjust heating, cooling and lighting according to occupancy, shaving energy use without compromising comfort. Urban planners are beginning to use AI to model how rising sea levels, flooding or heatwaves might affect future developments, allowing cities to adapt before crises strike.
Think of AI less as a futuristic add-on and more as the quiet, invisible engineer — optimising daily life in ways most residents will never notice, but the planet certainly will.
🔎 Further reading: Why AI's role in improving sustainability is underestimated | World Economic Forum
4. Rethinking how we feed the planet
Agriculture accounts for almost a third of global emissions, and yet demand for food is still climbing. AI is beginning to show how we might square that circle.
In the field, sensors and drones can guide farmers on exactly how much water or fertiliser a crop needs, preventing waste and improving yields. AI-equipped machinery, like John Deere’s precision planters, can target individual plants rather than treating entire fields, reducing chemical use dramatically. At the other end of the chain, algorithms can fine-tune supply logistics, tackling the staggering 1.3 billion tonnes of food wasted globally each year.
The promise is not just efficiency for its own sake, but the possibility of a food system that nourishes more people with a lighter environmental footprint.
5. Accelerating the breakthroughs we haven’t yet made
The most profound role AI might play is not in optimisation, but in discovery. Many of the technologies needed to cut emissions - from advanced batteries to scalable carbon capture - are still in development. AI can help bring them forward.
DeepMind’s AlphaFold, which cracked the decades-old puzzle of protein folding, is already being used to explore bio-based alternatives to plastics and more sustainable materials. In climate modelling, AI-enhanced simulations can produce robust projections in a fraction of the time traditional models require, giving policymakers tools to plan more effectively.
In essence, it’s a research accelerator: compressing decades of trial-and-error into years, and years into months. For a crisis in which time is our scarcest resource, that acceleration could prove decisive.