Assessing the Feasibility of Retrieval Augmented Generation for Materiality Analysis

Materiality assessment plays a critical role in sustainability reporting by identifying and prioritizing the most significant topics relevant to an organization and its stakeholders. As companies face increasing pressure to provide transparent and accountable disclosures, especially regarding environmental, social, and governance (ESG) issues, efficient and accurate materiality evaluations have become essential. This project focuses on prototyping and validating a scalable, automated framework that leverages a retrieval-augmented generation (RAG) approach to identify and rank material topics. By combining quantitative metrics and strong comparison methods, this approach aims to enhance the consistency and reliability of materiality rankings. This will ultimately help in making better decisions for sustainable business practices.