Accounting for Purchased Artificial Intelligence Inference in Corporate Greenhouse Gas Inventories: A Token-Based Method

The paper proposes a token‑based method for including purchased AI inference in corporate Scope 3 greenhouse gas inventories, offering a structured four‑term factor that accounts for serving electricity, embodied hardware, data‑centre construction, and disclosed training runs. It provides an open dataset with cradle‑to‑gate boundaries, four tiers of activity data, and a rule to map model identifiers and regions to specific factors, revealing up to twelve‑fold variation between model classes and nine‑fold variation between regions. Example calculations show annual emissions of 8.5 kg CO₂e for a 200‑person firm and 2.1–8.3 t CO₂e for developers using mid‑class or frontier‑class models, respectively.

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