Streamlining ESG reporting : leveraging generative AI for efficient PDF generation and editing | |
| Author | Mercier, Cedric Le |
| Call Number | AIT RSPR no.DSAI-24-05 |
| Subject(s) | Generative artificial intelligence Corporation reports--Data processing Sustainable development reporting |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence |
| Publisher | Asian Institute of Technology |
| Abstract | Automating and enhancing Environmental, Social, and Governance (ESG) reporting and analysis remains a challenging problem in Natural Language Processing (NLP). Numerousrelated works have attempted to address this issue by employing conventional ESG reporting software and AI-driven analytical tools.However, existing solutions face challenges in both report generation and analysis. The complexity of data interpretation, along with the need for consistency and comparability across reports, poses significant hurdles for sustainability professionals and analysts. Moreover, reliance on third-party rating agencies can lead to opacity and inconsistencies in assessment methodologies. This study investigates a novel platform that leverages generative AI technology to streamline ESG reporting and analysis for companies.The proposed platform integrates an ESG Data Platform for inputting sustainability goals, a generative AI model powered by GPT-4 for text generation, and a comprehensive report generation tool capable of pro ducing visually appealing PDF reports. Additionally, an AI-powered ESG rating tool facilitates efficient evaluation of ESG performance metrics.The key contributions of this paper are as follows: (1) Introducing a novel software concept for automating ESG reporting and analysis using generative AI technology, (2) Demonstrating the effectiveness of the proposed solution in enhancing the accessibility, efficiency, and accuracy of ESG reporting, and (3) Empowering small to medium-sized businesses in their sustainability endeavors through innovative technological solutions. |
| Year | 2024 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Data Science and Artificial Intelligence (DSAI) |
| Chairperson(s) | Chaklam Silpasuwanchai; |
| Examination Committee(s) | Attaphongse Taparugssanagorn;Chantri Polprasert; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Research Studies Project Report (M. Eng.) - Asian Institute of Technology, 2024 |