AI for Green Initiatives
AI has a huge potential in helping to reach climate commitments. When used properly, AI for Green has the potential to enhance the sustainability of our societies. In combination with the mitigation of the negative impacts of AI, this might enable enormous progress in working towards the ecological and digital transitions.
For the common adoption of AI solutions which greatly increase environmental sustainability, this inventory of AI use cases brings visibility to AI for Green collaborative projects that aim to meet environmental goals.
These projects were selected following consultation with members of the Coalition for Sustainable AI. They are organised into sub-categories derived from the United Nations Sustainable Development Goals, that correspond to the issues they address.
Decarbonized Energy
Predict carbon from landfills
Predict carbon resources in landfills for renewable energy storage, providing critical tools and datasets for overcrowded African cities.
Case studies collection of AI deployment across energy sector
Creation of a library of AI use cases in the field of energy as part of the “energy and AI” report (April 2025).
Project Sunroof
AI-driven solution that aims to make the process of installing solar panels easier and more undestandable for people, by using Google maps data.
Agriculture and Food
Accelerator Labs Network
Using AI to analyze earth observation data (satellite data and drone data) for crop disease detection, waste monitoring, land use mapping.
Optimize fertilizer usage
Provide real-time, lab-accurate soil data and AI-driven actionable recommendations, helping farmers improve yields while cutting fertilizer costs and carbon footprints.
Agrifood Systems Technology and Innovation Outlook (ATIO)
ATIO has two key components:
– a biennial publication starting in 2025, compiling the latest developments in science and technology relevant to agrifood systems.
– an open-source database dedicated to technologies and innovations for agrifood.
AI in Crop Yield Forecasting
Working with a private plantation company in Sri Lanka, GGGI aims to enhance sustainable agricultural practices and increase economic resilience for local communities by utilizing machine learning models for predicting tea yield prediction.
Agricultural AI agents
Develop a collaborative tool to generate AI agents specialized in agriculture, offering an open-source kit for creating AI solutions in the agricultural sector.
Trase for tropical deforestation
Trase maps the international trade and financing of commodities such as soy, beef and palm oil, enabling companies, investors and governments to address tropical deforestation.
Biodiversity
Mapping World’s Forest
Create the first global one-meter resolution tree canopy height map, enabling individual tree detection worldwide to improve carbon removal projects and forest monitoring.
Monitor biodiversity
Accelerate the effective conservation and regeneration of biodiversity and ecosystem health by strengthening the monitoring and understanding of the effects of climate change on priority ecosystems and species.
Monitor the Amazon deforestation
Monitor deforestation and protect biodiversity in the Amazon, enabling faster and more effective conservation efforts, through the use of cloud technology.
Detect illegal deforestation
Detect illegal logging in audio recordings of the jungle to help deploy rangers to locations where it happens in real time.
Trase for tropical deforestation
Trase maps the international trade and financing of commodities such as soy, beef and palm oil, enabling companies, investors and governments to address tropical deforestation.
Coral reef restoration Program
Tēnaka’s coral reef restoration helps protect and preserve critically important and endangered wildlife by using an underwater monitoring device and computer vision.
Oceans
AI for Blue Shores
An in-house AI-powered waste traceability platform designed for coastal areas, integrating geotagged collection data from fisherfolk retrieving ocean-bound plastic. It promotes plastic recovery, drives behavioral change, and supports ocean conservation while generating economic opportunities.
Ocean ecosystems modeling
Unravel the complexities of global ocean symbiomes, advancing understanding of marine ecosystems, climate change, and biodiversity, with the help of advanced mathematical modeling.
Machine learning for identifying marine species
An innovative algorithm capable of dynamically recognising the most common invasive Mediterranean fish species in Maltese coastal waters, based on available images. Machine learning models and transfer learning were utilised to facilitate precise, real-time species identification.
Marine protection of sensitive zones
Using AI-driven satellite image analysis for marine protection, addressing illegal fishing, terrorism, and biodiversity preservation, while assessing climate change impacts on coastal areas.
AI to fight illegal fishing
Not-for-profit organisation which helps preserve marine biodiversity, protects livelihoods and prevents slavery in the seafood industry, using satellites and artificial intelligence (AI), to identify fishing activities and suspected non-compliance, helping to protect the world’s vast oceans.
AI in Blue Carbon monitoring
In the context of Indonesia’ Ministry of Marine Affairs and Fisheries’ (MMAF) mandate to implement a robust carbon pricing mechanism that includes blue carbon ecosystems, GGGI is working to pilot a remote sensing-based seagrass mapping tool for costal seagrass monitoring
Climate Action through Artificial Intelligence and Data Innovation for Caribbean SIDS
Evidence-based Climate Action through Artificial Intelligence and Data Innovation for Caribbean SIDS, is a project focused on using AI and data to enhance climate action in the Caribbean.
It aims to improve the ability of four Caribbean Small Island Developing States (SIDS) to monitor and analyze maritime transport, trade, fisheries, and their greenhouse gas (GHG) emissions.
Decarbonization and global warming
Decarbonization of industies
Help industries transform digitally and sustainably by optimizing production processes, reducing carbon emissions, and improving energy efficiency with real-time monitoring and predictive maintenance tools.
Detect climate desinformation
Detect climate-based misinformation in the input text and to categorize it into one of the 8 categories of climate misinformation.
International Methane Emissions Observatory
An Observatory that produces empirical data on methane emissions by using AI, to enable climate action at scale.
Climate TRACE
AI to monitor CO2 emissions : track shipping sector emissions from container ships, tankers, cruise ships, and other large vessels — to support industry decarbonization.
Prithvi WxC – AI model for weather and climate
An open-source foundation model that can be customized for a variety of weather and climate-related applications — and run on a desktop computer. The model is able to reconstruct global surface temperatures.
Chatbot for ecological transition
A trusted chatbot for the ecological transition, based on data from various French public players. A public solution based on AI that is able to deliver informations on ecological transition for public officials.
Reduce transport emissions
Project Green Light uses AI to help city traffic engineers optimize traffic lights at intersections to improve traffic flow and cut emissions. With this information, cities can make cost-effective updates to existing infrastructure to reduce the number of stops cars make at red lights.
Classify regions at risk of wildfires
Automatically locate smoke on videos from cameras located in the forest, before it becomes an out-of-control wildfire.
Sustainable cities and communities
AI to help cities tackle extreme heat
Heat Resilience tool applies AI to satellite and aerial imagery, helping cities to quantify how to reduce surface temperatures with cooling interventions, like planting trees and installing highly reflective surfaces like cool roofs.
Monitor air quality
Real-time sampling and microscopic imaging of airborne particles with the aim of providing innovative prevention services (respiratory risks, industrial risks, biological risks to human, plant, and animal health, environmental protection).
Reduce transport emissions
Project Green Light uses AI to help city traffic engineers optimize traffic lights at intersections to improve traffic flow and cut emissions. With this information, cities can make cost-effective updates to existing infrastructure to reduce the number of stops cars make at red lights.
Computer vision to detect litter
AWIGS (Aerial Waste Identification and Geolocation System): in collaboration with the CMD (Cleansing and Maintenance Division) department, a team of researchers is exploring the use of drones equiped with computer vision to detect litter in areas that are otherwise inaccessible or difficult to monitor, such as nature reserves, cliff sides, remote beaches, and Natura 2000 sites.
Early Warnings for All (EW4All) Initiative
Early Warnings for All (EW4All) Initiative, supported by ITU (pillar 3), seeks to establish comprehensive global protection through early warning systems by 2027. ITU is leading the Warning Dissemination and Communication pillar of the EW4All initiative, to look at last-mile connectivity and to ensure that warnings reach the people at risk in time to take action.
Water, floods, desertification
Desert locust prediction
Desert locust swarms pose a significant threat to agriculture and food security. The study introduces an operational model for predicting locust breeding areas, aiming to improve early warning systems and targeted control efforts.
Flood Map Prediction & Water Scarcity
A hackathon and a datascience challenge to develop a map for floods prediction using AI, but also water scarcity in water-stressed areas.
Prioritize interventions for floods
Better prepare for floods through more robust flood planning and management activities with Satellite and weather data; demographic vulnerability data; access to infrastructure data; losses and damages data; and government response data.
Disaster management
Global Initiative on Resilience to Natural Hazards through AI Solutions
The initiative aims to explore how AI can be effectively used in disaster management, providing expert guidance and support for research, innovation, and the development of standards.
Early Warnings for All Initiative
The Early Warnings for All (EW4All) initiative aims to ensure universal protection from hazardous hydrometeorological, climatological and related environmental events through life-saving multi-hazard early warning systems, anticipatory action and resilience efforts
