data jungle adventures

From predicting wildfires to powering smart cities, Artificial Intelligence (AI) is being cast as the climate superhero of the 21st century. It’s crunching climate models, tracking endangered species (including us humans), and helping us squeeze more power from the sun and wind. Sounds like the ultimate green tech dream, right? Well… not so fast. As AI flexes its digital muscles, it’s also raising some serious environmental red flags. The question is no longer if AI will impact our planet—but how. And whether that impact will be for better… or worse.

The Promise of AI in environmental stewardship

Advocates point to a growing range of AI applications supporting environmental protection and climate adaptation. Tech companies and research institutions are already using AI to track deforestation, monitor extreme weather events, forecast droughts, and detect pollution leaks. Google, for instance, claims that AI could help reduce global emissions by as much as 10% by 2030—roughly equivalent to the European Union’s entire annual emissions.

Renewable energy systems can benefit from AI-powered forecasting of weather and energy demand, optimizing energy distribution and reducing reliance on fossil fuels. Smart grids and building management systems powered by AI are improving energy efficiency in urban areas. AI-driven tools also enable better climate modeling, which helps governments and communities plan for long-term climate resilience.

AI’s acceleration effect—the ability to do more, faster—also opens the door to early detection of wildfires, flood prediction, tracking endangered species, and enforcement against illegal fishing. These examples prove that AI can significantly bolster mitigation and adaptation strategies when designed with care.

The Peril: growing footprint and misinformation threats

Yet a growing coalition of environmental organizations is urging caution. A recent report from the Climate Action Against Disinformation coalition warns that the current AI trajectory may increase—not decrease—planet-warming emissions. This paradox stems from the enormous energy demands of AI systems, particularly training large language models and maintaining vast data centers. Some projections suggest that by 2026, AI servers alone could consume as much energy as the entire nation of Sweden.

The U.S. has already witnessed coal plants being kept operational to meet new AI-related electricity demands, calling into question whether AI will displace outdated technologies—or entrench them further. The development and training of models like ChatGPT reportedly consumes the equivalent annual energy use of more than 100 U.S. households.

Compounding the issue is AI’s potential to spread climate disinformation at scale. As social media platforms struggle to regulate false narratives, AI tools risk amplifying them—producing deepfake videos, misleading content, and micro-targeted campaigns that distort public understanding of climate science. According to Friends of the Earth’s Michael Khoo, “AI is perfect for flooding the zone with quick, cheaply produced disinformation.”

Responsibility and a path forward

Technology, including AI, is inherently neutral; its environmental and social impacts depend entirely on how it is designed, deployed, and governed. Depending on applications, data sources, and underlying incentives, AI can either exacerbate environmental harms or help mitigate them. For instance, AI systems themselves contribute to carbon emissions, often significantly. One practical step toward responsible AI is to integrate energy-aware decision-making: for instance, models could estimate the CO₂ cost of each query or inference and prioritize the most energy-efficient computation paths. Selecting lightweight models or sustainable data centers for specific tasks could become part of the environmental management strategy.

But, to ensure AI serves as a force for good in the climate fight, deliberate and responsible strategies must be adopted. First, AI development and deployment should prioritise energy efficiency, from training algorithms to deploying models at scale. Second, robust governance frameworks are essential to guide ethical and effective use of AI in climate-related domains. Third, targeted investment is needed in AI tools designed specifically to combat climate misinformation, ensuring accurate and science-based communication. Finally, transparency and accountability in how AI is used in sustainability efforts will be key to building trust and ensuring that AI contributes meaningfully—not superficially—to global climate goals.

Despite the risks, experts like Jesse Dodge from the Allen Institute for AI remain “cautiously optimistic.” He argues that while AI’s energy and water footprint is real, its net benefit depends on how the technology is applied. With dedicated teams already working on using AI for wildfire prediction, wildlife monitoring, and climate risk analysis, there’s hope that responsible deployment can outweigh the harms.

Conclusion: a double-edged sword

While AI is often promoted as a solution for environmental management, it is important to avoid ‘technologism’—the belief that technological innovation alone can solve complex ecological problems. Deploying AI without a critical framework may lead to technology-driven solutions that overlook social, ethical, or systemic factors. Technology should serve clear environmental goals, not become an end in itself.

And while AI holds promise for climate change mitigation, it’s crucial to approach its development and deployment thoughtfully. By addressing the energy intensity of AI systems and their potential to spread misinformation, we can work towards harnessing AI as a powerful tool in the fight against climate change, rather than an additional burden on our planet’s resources.

Feature image generated by MetaAI