Carbon Footprint of AI
The total greenhouse gas emissions produced by training, deploying and running AI models, including the energy consumed by data centres and hardware manufacturing.
In plain language
The environmental cost of running AI systems. Training a large language model consumes enormous amounts of electricity and generates significant carbon emissions, comparable to the lifetime emissions of multiple cars.
Why this matters
As ESG reporting requirements tighten, organisations must account for the carbon footprint of their AI operations. Your governance framework should include environmental impact assessment and tracking as part of responsible AI practice and stakeholder accountability.
Relevance
GovernanceCarbon footprint reporting is an increasingly material ESG governance requirement for organisations deploying energy-intensive AI systems.
Related terms
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