How IBM Envizi can calculate Scope 3 emissions
IBM has introduced an innovative solution for calculating Scope 3 emissions using AI and Large Language Models (LLMs). Scope 3 emissions, which include indirect emissions from a company’s value chain, are notoriously challenging to estimate. Traditional methods are often time-consuming and resource-intensive.
The new approach within IBM Envizi utilises LLMs to categorise financial transaction data, aligning it with spend-based emissions factors. This AI-driven process simplifies the complex task of mapping purchase orders and ledger entries to specific emission categories, dramatically accelerating the time to insight.
A key component of this solution is the fine-tuning of foundation models for natural language processing (NLP), which allows for accurate classification and emission computation. This integration not only improves the accuracy of Scope 3 emissions estimates but also enhances the efficiency of data processing.
The benefits of this innovative approach are embedded into the IBM Envizi ESG Suite, providing businesses with an AI-driven feature that automates the recognition of commodity categories from spend transaction descriptions. This streamlines the process of estimating Scope 3 emissions and helps organisations manage their environmental impact more effectively.
Incorporating advanced AI technologies into sustainability efforts exemplifies IBM’s commitment to innovation and environmental stewardship. By leveraging the power of LLMs, IBM Envizi enables companies to better understand and mitigate their indirect emissions, supporting global sustainability goals.
This story is inspired by an IBM Blog post.
