Inventory of reports on Sustainable AI
Discover a selection of scientific articles on sustainable AI published by our members. This page brings together publications essential to understanding advances, challenges and best practices in the design, use and environmental impact of artificial intelligence.
Opinions expressed in these reports are those of the issuing organization and do not necessarily reflect the views of the members of the Coalition.
List of key readings
Semiconductor Emission Explorer: Tracking Greenhouse Gas Emissions from Chip Production (2015-2023)
Analysis of greenhouse gas emissions from global chip manufacturers between 2015 and 2023, highlighting key trends and the need for improved reporting standards.
Artificial intelligence, data, computation: what infrastructure for a low-carbon world?
An interim report exploring the environmental impact of AI and data centers, focusing on energy consumption and carbon emissions.
Artificial Intelligence and electricity: A system dynamics approach
A detailed examination of how artificial intelligence affects electricity consumption, exploring various scenarios and sustainability implications.
Energy and AI
A detailed analysis of the ICT sector’s electricity consumption, highlighting that while data traffic has grown exponentially, energy use has increased only modestly due to efficiency improvements, with future growth influenced by AI developments.
Energy and AI
This report aims to fill this gap based on new global and regional modelling and datasets, as well as extensive consultation with governments and regulators, the tech sector, the energy industry and international experts. It includes projections for how much electricity AI could consume over the next decade, as well as which energy sources are set to help meet it. It also analyses what the uptake of AI could mean for energy security, emissions, innovation and affordability.
Please find a comprehensive list of key papers for decision-makers
on the environmental sustainability of AI by visiting our dedicated page.
