Sustainability Report

Sustainability reports, crucial for assessing corporate environmental and social responsibility, are increasingly scrutinized for accuracy and completeness. Current research focuses on leveraging large language models (LLMs), such as BERT and variations like ClimateBERT, and retrieval-augmented generation (RAG) to automate the analysis of these reports, detect greenwashing, and extract structured insights on ESG factors. This automated analysis aims to improve transparency and efficiency, empowering stakeholders with data-driven assessments of corporate sustainability practices and informing more effective regulatory oversight. The development of these AI-powered tools is further enhanced by incorporating domain expertise and multi-objective optimization techniques to balance sustainability goals with consumer preferences.