The Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints
The Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints
Publish Date: 2026-06-03 10:13:00
Source Domain: unu.edu
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Environmental Impact of AI Energy Use: The UNU-INWEH report highlights the environmental costs, including carbon, water, and land footprints, associated with the energy required to power artificial intelligence (AI) systems.
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Beyond Carbon Footprint: While focusing on carbon emissions, the report also measures water and land implications of AI energy use, showing that low-carbon electricity may not equate to low resource use.
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Influence of Electricity Sources: AI’s environmental costs depend heavily on where electricity is generated and the energy sources used. Not all low-carbon electricity is equally sustainable in terms of water and land use.
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AI Infrastructure and Footprints: The expansion of AI infrastructure (data centers, cooling systems, etc.) contributes significantly to its environmental footprint.
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Integration into Planning: The report stresses the necessity to integrate AI’s environmental footprints into energy, climate, water, and land-use planning to mitigate environmental burdens.
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Governance and Justice: The report frames AI’s environmental footprint as a governance and justice issue, stressing equitable distribution of both benefits and burdens of AI technology.
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Recommendations for Sustainable AI: The report calls for creating a responsible AI ecosystem with a focus on transparency, efficiency, global cooperation, and sustainable use to ensure AI’s advancement does not disproportionally impact vulnerable communities.
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Holistic Environmental Approach: AI cannot be viewed solely as a digital technology; it requires a comprehensive approach that considers its material and environmental impacts.
