Methodology update: Starting with January 2026 data, we have updated our

## Feature Feature **Methodology update**: Starting with January 2026 data, we have updated our calculation model to align with the comprehensive AI energy/emissions framework detailed in[Measuring the environmental impact of delivering AI at Google Scale](https://cloud.google.com/blog/products/infrastructure/measuring-the-environmental-impact-of-ai-inference). This update allocates previously unallocated AI inference model emissions to the associated Google Cloud services, following the SKU-level allocation described in the[Carbon Footprint reporting methodology](https://docs.cloud.google.com/carbon-footprint/docs/methodology). This change is part of our ongoing effort to provide more accurate and transparent emissions data for AI inference. **Impact**: Customers will see an increase in reported emissions for services that utilize AI model inference across all SKUs. Such an increase is spread across all SKUs within those services, based on the SKU-level allocation[methodology](https://docs.cloud.google.com/carbon-footprint/docs/methodology#sku-allocation). The primary impact is on Vertex AI. Other impacted services include Video Stitcher API, Notebooks, Cloud Natural Language, Cloud Speech API, Cloud Document AI API, Cloud Dialogflow API, Cloud Machine Learning Engine, Cloud Text-to-Speech API and Cloud Vision API.