Sustainability & AI
Life-cycle assessment of AI
Assessing AI systems' environmental impacts from raw-material extraction through manufacture, use and end of life.
Definition
Applying life-cycle assessment methods to AI systems — quantifying environmental impacts from raw-material extraction through hardware manufacture, training, use and end of life.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Established
- Last updated
- 21 August 2026
References
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Overview
What it means
LCA extends AI accounting beyond electricity: embodied emissions and resource use of chips and servers, infrastructure construction, and disposal all enter the boundary. ITU-T L. 1410 provides the methodology for ICT goods, networks and services; academic studies of large models (e. g. Luccioni et al. on BLOOM) demonstrate cradle-to-grave estimates.
How it is used
Practitioners use AI LCA to compare deployment options, inform procurement and avoid burden-shifting — for example, cutting operational energy by using more hardware. Corporate inventories apply it to ICT estates generally, with AI workloads an increasing share.
Why it matters
Operational-only accounting misses a large and growing slice of AI's impact. LCA disciplines the comparison between AI's environmental costs and benefits — and exposes when 'efficient AI' claims ignore what it took to build the machine.
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