Resources in AI and Sustainability

We provide these resoures in the context of the AI Action Summit (Paris 2025), to provide guidance for heads of state and governments looking to steer AI towards beneficial impact.

Selected organizations that facilitate work in AI and climate or provide thought leadership in this space (listed in alphabetical order):

• AfriClimateAI
• Centre for AI and Climate (CAIC)
• Climate AI Nordics
• Climate Change AI (CCAI) - this organization
• Climate Informatics
• Coalition for Digital Environmental Sustainability (CODES)
• Computational Sustainability
• Global Partnership on AI - Project RAISE
• Green Screen Coalition
• Green Web Foundation
• OECD.AI Expert Group on AI Compute and Climate
• Sustainable AI Coalition
• TEC-CTCN AI4ClimateAction Initiative

Note that this list is not intended to cover specific AI-for-climate projects, companies, or research initiatives.

Key readings on AI and sustainability for international decision-makers:

• Climate Change and AI: Recommendations for Government Action, Global Partnership on AI report.
• Biodiversity and AI: Opportunities and Recommendations for Action, Global Partnership on AI report.
• Aligning Artificial Intelligence with Climate Change Mitigation, Nature Climate Change.
• Measuring the Environmental Impacts of AI Compute and Applications, OECD Digital Economy Papers.
• Power Hungry Processing: Watts Driving the Cost of AI Deployment?, Proceedings of the ACM Conference on Fairness, Accountability, and Transparency.
• Tackling Climate Change with Machine Learning, ACM Computing Surveys.
• AI for Climate Change Mitigation Roadmap, ICEF report
• Landscape Assessment of AI for Climate and Nature, Columbia Climate School
• Machine Learning for Sustainable Energy Systems, Annual Reviews.
• Pushing the frontiers in climate modelling and analysis with machine learning, Nature Climate Change.
• The potential for AI to revolutionize conservation: a horizon scan, Trends in Ecology and Evolution.
• How to estimate carbon footprint when training deep learning models? A guide and review, Environmental Research Communications.
• A systematic review of Green AI, WIREs Data Mining and Knowledge Discovery

Contact info@climatechange.ai if you would like to suggest additions or changes to this page.