Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reporting
arXiv:2606.10660v1 Announce Type: cross Abstract: AI inference services -- API subscriptions, enterprise chat tools, and SaaS products with embedded AI features -- fall unambiguously within Scope 3 Category 1 under the Corporate Sustainability Reporting Directive (CSRD), which requires disclosure for fiscal years starting January 2024. Yet no standardised methodology exists for including them in corporate GHG inventories. Current practice either omits the category entirely or applies a generic economic input-output (EEIO) factor calibrated to the ICT sector as a whole, overestimating AI infere
The Corporate Sustainability Reporting Directive (CSRD) came into effect for fiscal years starting January 2024, immediately increasing demand for standardized GHG accounting for AI inference services.
This paper addresses a critical gap in corporate sustainability reporting, pushing companies to accurately quantify the previously hidden environmental impact of their AI usage under Scope 3 Category 1.
Companies can no longer ignore or broadly estimate the carbon footprint of their AI inference services; a specific methodology will likely become standard, leading to increased disclosure and pressure for efficiency.
- · Sustainability reporting software companies
- · Carbon accounting consultants
- · Cloud providers specializing in green AI infrastructure
- · Companies with energy-efficient AI operations
- · Companies with high-carbon AI inference footprints
- · Providers of inefficient AI services
- · Companies that have not prioritized AI carbon accounting
Companies will begin to implement the proposed four-tier methodology or similar frameworks to account for AI inference in their GHG inventories.
Increased transparency regarding AI's carbon footprint will drive demand for more energy-efficient AI models, algorithms, and underlying compute infrastructure.
The carbon cost of AI could become a competitive differentiator, impacting procurement decisions for AI services and influencing investment in green AI research and development.
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Read at arXiv cs.AI