risk
Environmental footprint of AI training and infrastructure
Training and large-scale inference consume disproportionate energy and generate greenhouse-gas emissions; rapid AI-hardware obsolescence produces e-waste and pressures critical-mineral supply chains, with environmental and geopolitical risk.
In catalog since 2026-09-17T22:28:00Z · Last changed 2026-09-17T22:28:00Z (f368a6cce277)
Record JSON · Open in map · Data retrieval guide
Catalog revision: 791ff2dd3a45707290badee660f185e514d15f1cf518908628f425c2f2c56ee4. A connection does not establish full coverage.
Attributes
- category
- esg
- domain
- AI Governance
- Risk Assessment & Management
- taxonomy
- iso-23894-ai-risk
- inherent_rating
- low
Details
- risk_id
- ai-environmental-footprint
- category
- esg
- likelihood
- medium
- impact
- low
- inherent_rating
- low
- treatment
- mitigate
- taxonomies
- iso-23894-ai-risk
Source
No record-specific source URL is provided.
Connections
- UC-AI-03 — Document AI system resources and dependencies mitigates Environmental footprint of AI training and infrastructure
- strength
- related
- rationale
- Inventorying computing/system resources gives the footprint visibility needed to measure and manage AI energy/compute consumption.
- UC-RISK-13 — Monitor and review risk management performance mitigates Environmental footprint of AI training and infrastructure
- strength
- related
- rationale