aceThe carbon and water footprints of data centers and what this could mean for artificial intelligence
Although there are ways to estimate the global power demand of artificial intelligence (AI) systems, it remains challenging to quantify the associated carbon and water footprints. The lack of distinction between AI and non-AI workloads in the environmental reports of data center operators makes it possible to assess the environmental impact of AI workloads only by approximating them through data centers' general performance metrics. The environmental disclosure of tech companies is, however, often insufficient t…
AI workloads' environmental impact is growing rapidly but remains hard to quantify because data center operators do not separate AI and non-AI reporting, with AI alone projected to reach 32.6-79.7 million tons CO2 and 312.5-764.6 billion liters of water in 2025.
Quantification remains approximate because operators do not distinguish AI from non-AI workloads and disclosures are insufficient to determine total data center performance.
Evidence
- Peer-reviewedPatterns2025-12-17
How should this claim be treated?
Truvace Impact Record TRV-2026-0433, v1: “The carbon and water footprints of data centers and what this could mean for artificial intelligence.” Truvace, 2026-07-20. /record/TRV-2026-0433 (accessed at citation time). sha256 9ac18e080b4c1913…
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