This project aims to enhance awareness and improve understanding of the environmental implications of AI systems that use massive computational resources, and therefore raise sustainability concerns. By measuring and reducing AI’s potential negative effects, while also leveraging its capabilities to drive positive change for the planet, we seek to advance sustainable development.

The positive and negative effects of AI computing and applications on the planet: what is needed to measure AI’s environmental footprint.

The OECD.AI Expert Group on AI and Climate, together with experts from the Responsible AI Working Group of the Global Partnership on AI under Project RAISE, have developed an overview of existing and emerging proxies, indicators, metrics, and tools to help measure the environmental impacts of AI compute and applications.

The green and digital “twin transitions” promise to leverage digital technologies for a sustainable future. As a general-purpose technology, artificial intelligence has the potential not just to promote economic growth and social well-being, but also to help achieve greater global sustainability as the world undergoes mass digitalisation. However, training and deploying AI systems can require massive amounts of computational resources with their own environmental impacts through energy and water use, GHG emissions, and overall life cycle impacts.

To fully harness AI technologies to achieve domestic economic growth goals and to help meet national and global sustainability goals, policymakers, civil society and private sector actors need accurate and reliable measures of the environmental impacts of AI.

Launched and presented at COP27, the report also proposes an analytical framework to help quantify the environmental footprint of AI. A growing number of actors recognise the dual impacts of AI compute and applications, advocating for AI to be channelled to harness the immense opportunities for environmental sustainability while concurrently minimising negative effects. These efforts will require cross-disciplinary efforts by scientists, policymakers, civil society, the private sector, technologists and more.


Stephanie King


Director of AI Initiatives

Arnaud Quenneville-Langis


Project Manager

Johannes Leon Kirnberger


Project Manager