Environmental footprint of AI
Training and operating AI systems consume substantial energy, water, and materials, producing carbon emissions, e-waste, and ecosystem harm.
- Risk family
- Governance & process
- MIT domain
- 6. Socioeconomic and Environmental
- MIT subdomain
- 6.6 > Environmental harm
- AI type
- GPAI, Classical_ML, Agentic
- Scope
- Both
- Source standard
- MIT AI Risk Repository v4
Provenance
28 source framework citation keys
Framework crosswalk
Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.
- A.5 ISO/IEC 23894 Annex A A.5
- A.4.5 ISO/IEC 42001 Annex A A.4.5
- ibm-ai-agents-impact-on-environment AI agents' impact on environment
- ibm-impact-on-the-environment Impact on the environment
- ibm-redundant-actions Redundant actions partial
- GENAI.5 Environmental Impacts
More in Governance & process
Part of the Deployer AI Risk Register, an open-source resource developed by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.