We, the members and supporters of the Coalition for Sustainable AI, affirm our collective commitment to leverage the development and use of artificial intelligence (AI) to progress towards the UN Agenda 2030 and the Sustainable Development Goals (UN SDGs), focusing in this Coalition on those related to climate action and protection of our environment.

The transformative potential of AI in tackling the climate and environmental crisis is already unfolding. For example, AI-driven technologies can optimize energy grids, enable precision agriculture, monitor deforestation, and accelerate the transition to low carbon energy systems. These capabilities can significantly contribute to reaching net zero greenhouse gas emissions, preserving biodiversity and protecting our oceans.

At the same time, the environmental footprint of AI itself is already growing and is expected to increase. The processes associated with AI—from its hardware and its software cycle—pose significant environmental challenges. Therefore, it is imperative to ensure that AI is developed and deployed respecting the ecological limits of our planet.

To ensure AI contributes positively to environmental and climate objectives and can be deployed at scale, we:

1. Encourage AI Initiatives for the Planet: We commend inclusive and collaborative efforts to harness AI for the benefit of the local and global environment, including its role in decarbonizing economies, reducing pollution, preserving biodiversity, protecting the oceans, and ensuring humanity operates within planetary boundaries.
2. Wish to continue our work for an AI respectful of our Planetary Boundaries: To this end, we understand the need to focus on the following:
   • Standardized methods and metrics for measuring AI’s environmental impacts: We advocate for the development of consistent methods to better assess AI’s environmental impacts, notably on energy consumption.
   • Comprehensive Life Cycle Analysis: AI systems should be evaluated across their entire life cycle through multi-criteria analysis. For software, this includes data collection, model development, training, deployment, and maintenance. For hardware, this involves mining and extraction practices, transportation, energy and water use, and waste management, including e-waste generation.
   • Frameworks for Reporting and Disclosure: Mechanisms should be established for companies to transparently report the environmental impact of their AI products and services.
   • Prioritization of Research on Sustainable AI: The private sector and research community should prioritize developing AI technologies with optimized algorithms to reduce computational complexity and minimize data usage.
   • Efforts that ensure AI infrastructure and software are built and maintained in line with global environmental commitments.
3. Support Collaborative Approaches: We recognize the essential role of multi-stakeholder collaboration—bringing together governments, academia, civil society, and the private sector—to advance these objectives. By pooling our knowledge and resources, we can ensure AI becomes a force for sustainability and a cornerstone of the global response to the triple planetary crisis of climate change, biodiversity loss and pollution.

We stand united in our vision for a sustainable AI to support our collective efforts to address environmental challenges, while securing a sustainable legacy for future generations.