Fighting climate change with the power of AI

As the effects of climate change accelerate across the globe, threatening ecosystems, economies and communities, it becomes increasingly clear that every available tool must be brought to bear in the effort to confront this crisis. From policy shifts and lifestyle changes to technological innovation, the solutions must be as varied and dynamic as the problems they seek to address. One of the most promising and fast-evolving tools in our arsenal today is artificial intelligence.

While AI has often been more associated with advancements in productivity, robotics and automation, it is also uniquely suited to tackle the multifaceted and data-heavy challenges posed by climate change. AI is not a silver bullet, but it is a potent weapon in the global climate arsenal — capable of revolutionizing how we model, understand and mitigate climate impacts. Ignoring its potential would be a grave oversight.

AI offers unmatched capabilities in terms of processing vast amounts of complex data, identifying patterns, making predictions and continuously improving outcomes based on feedback loops. In the context of climate change, where variables are numerous and interrelated — ranging from atmospheric conditions to energy systems and agricultural cycles — AI can provide insights that are often inaccessible through traditional means. As governments and organizations around the world search for scalable and effective responses to the climate emergency, integrating AI into climate strategy is not just an option, it is a necessity.

One of the most significant contributions AI can make in the fight against climate change is in enhancing climate modeling and forecasting. Traditional climate models are powerful but often limited by the sheer volume and variability of environmental data. AI algorithms, especially machine learning and deep learning models, can sift through terabytes of satellite imagery, weather station data and oceanographic information to detect trends, anomalies and potential future scenarios with unprecedented accuracy.

These capabilities are already being harnessed, with agencies such as the US’ National Oceanic and Atmospheric Administration incorporating AI into their climate prediction systems. More accurate forecasting means better preparation for climate-induced disasters such as hurricanes, droughts and floods — ultimately saving lives, reducing economic losses and informing more effective policy decisions.

In the energy sector, AI is proving instrumental in accelerating the transition from fossil fuels to renewable sources. By predicting energy demand, analyzing weather patterns for optimal solar and wind output and managing energy storage systems, AI ensures that renewable energy is delivered more efficiently and reliably. This has been particularly valuable in Brazil, where hydropower and wind energy make up a significant share of the country’s electricity production. AI tools help balance the grid, reduce energy waste and anticipate fluctuations in supply and demand. By integrating AI into its energy infrastructure, Brazil is not only lowering emissions but also improving energy access and stability for millions of people.

Agriculture is another domain where AI can dramatically reduce environmental impact. Agricultural activities contribute to greenhouse gas emissions through livestock, fertilizer use and land conversion. AI-driven precision agriculture tools can optimize water usage, reduce pesticide application and increase crop yields without expanding land use. In India, a country with a vast and diverse farming population, AI applications are being deployed to guide farmers on optimal planting times, crop rotation and irrigation schedules based on real-time weather and soil data. These interventions not only boost productivity but also promote sustainable practices that align with climate goals.

In the realm of waste management, AI is facilitating smarter and more efficient recycling systems. Traditional recycling processes are labor-intensive and often inaccurate in sorting materials. AI-powered systems, equipped with computer vision and robotics, can sort waste more accurately and at a much faster pace. In the UK, some companies are deploying AI to analyze and categorize waste on conveyor belts in recycling facilities. This not only increases the recycling rate but also ensures that fewer materials end up in landfills, where they can produce methane, a greenhouse gas many times more potent than carbon dioxide. Improved waste management also reduces the burden on municipal systems and contributes to a circular economy.

AI is also playing a critical role in environmental monitoring and conservation. From tracking deforestation and biodiversity loss to detecting illegal fishing and monitoring glacier retreat, AI systems provide timely and actionable data. For example, in the Netherlands, an AI-driven algorithm is being used to map concentrations of plastic in oceans and determine the most efficient paths for cleanup vessels. This targeted approach maximizes the effectiveness of cleanup efforts while minimizing fuel use and operational costs. These technologies can be replicated in other regions facing marine pollution crises, improving global ocean health and mitigating the broader environmental impact of plastic waste.

AI can empower both developed and developing nations to build a more sustainable and resilient future.

Dr. Majid Rafizadeh

In many vulnerable regions, particularly in the Global South, AI is enhancing climate resilience by supporting adaptation strategies tailored to local conditions. In several African nations, AI-driven platforms are helping communities better understand and prepare for climate risks such as desertification, water scarcity and extreme weather. These platforms analyze environmental and socioeconomic data to recommend sustainable farming practices, early warning systems and water management strategies.

In countries like Kenya and Ethiopia, where climate variability threatens food security and livelihoods, these AI interventions are empowering local populations with knowledge and tools to adapt effectively. This not only enhances resilience but also promotes equitable access to climate solutions in historically underserved regions.

In conclusion, if harnessed thoughtfully, AI can be a cornerstone of global climate strategy — one that empowers both developed and developing nations to build a more sustainable and resilient future. AI offers powerful and multifaceted tools that can significantly enhance our ability to combat climate change, from improving climate forecasts and optimizing renewable energy systems to transforming agriculture and waste management.

• Dr. Majid Rafizadeh is a Harvard-educated Iranian American political scientist. X: @Dr_Rafizadeh