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AI-enabled technologies have huge potential to support positive climate action. From digital twin technology that model the Earth, to algorithms to make data centres more efficient, AI applications already support the green transition. But AI systems also raise sustainability concerns linked to the natural resources they consume such as electricity and water, and the carbon emissions they produce. The rise of deep learning and large language models has also dramatically increased the amount of compute capacity AI systems need. As the use of AI increases, governments and policy makers need to understand AI’s environmental impacts so that they can make evidence-based decisions. This begs the question: what is AI’s environmental footprint? This panel discussion explores these issues through the launch of the report "The AI footprint: measuring the environmental impacts of AI compute and applications". Informed by experts from the OECD.AI Expert Group on AI Compute and Climate and the Global Partnership on AI (GPAI) Responsible AI Working Group (RAI), the report examines existing measurement tools and key challenges for quantifying the positive and negative environmental impacts of training and deploying AI models and their applications. By creating and tracking AI-specific measures of compute, sharing best practices, and supporting new and innovative AI applications for fighting climate change, countries can ensure that AI is trained and deployed in the most sustainable way possible, while minimising negative impacts, for the good of the planet.