📄 Sciences Methods and Technologies
International Journal (SciMeTech)

Volume 2 · Issue 1 · 2026
ISSN: 3085-5284
Bridging the ESG Disclosure Gap: GAED Framework, A Conceptual Model
L R Niranjan, Shivakami Rajan
Pages 55–60 · School of Business and Management, Christ University, Bangalore, India · Faculty of Management and Commerce, Ramaiah University of Applied Sciences, Bangalore, India
Abstract
The mandatory disclosure by corporates with reference to Environmental, Social, and Governance, especially in the emerging economies is complicated because of the data ecosystems, regulatory infrastructure and institutional capacities remaining uneven. Generative Artificial Intelligence (GenAI) is emerging as a transformative opportunity to bridge these structural lacuna. By automating the data collection process, enabling compliance mapping in real-time and strengthening the assurance of governance, the impact of GenAI is palpable. This work is an attempt to develop a conceptual framework to understand the role of GenAI as an enabler for ESG disclosure. Set in an emerging economy like India, the study is relevant in an evolving Business Responsibility and Sustainability Reporting (BRSR) landscape. A systematic review and thematic synthesis of recent research resulted in four dimensions that explain how GenAI supports ESG disclosure. The authors propose a Generative AI Enabled Disclosure (GAED) framework using the four dimensions of Data Integration, Framework Alignment, Narrative Generation and Governance Assurance. The study offers interventions that regulators and corporate sustainability practitioners may adopt as an intelligent infrastructure and not as replacement of human judgement. This makes ESG disclosure accessible, actionable and accountable.
Keywords: Generative AI, ESG Disclosure, Emerging Economies, BRSR, Sustainability Reporting, Digital Transformation

References

  1. Bag, S., et al. (2026). Generative AI, ESG sensemaking, and environmental performance: An OIPT perspective. Business Strategy and the Environment. https://doi.org/10.1002/bse.70520
  2. Chopra, S. S., et al. (2024). Navigating the challenges of environmental, social, and governance (ESG) reporting: The path to broader sustainable development. Sustainability, 16(2), 606. https://doi.org/10.3390/su16020606
  3. De Villiers, C., Dimes, R., & Molinari, M. (2024). How will AI text generation and processing impact sustainability reporting? Meditari Accountancy Research, 32(3), 739-768. https://doi.org/10.1108/MEDAR-06-2022-1694
  4. Dwibedi, P., Pahi, D., & Mishra, A. P. (2025). Corporate environmental, social, and governance disclosure and performance dynamics: An empirical analysis of BRICS nations. Indian Journal of Finance, 19(2), 27-44. https://doi.org/10.17010/ijf/2025/v19i2/174769
  5. EcoActive. (2025). The AI shift in ESG reporting: 6 trends sustainability teams cannot ignore. EcoActive Technology. https://ecoactivetech.com/ai-esg-reporting-trends-2025/
  6. Envoria. (2025). AI in ESG reporting: Reality, potential, and limitations. https://envoria.com/insights-news/ai-in-esg-reporting-reality-potential-and-limitations
  7. ESG Book. (2023). How generative AI enables corporate ESG reporting. https://www.esgbook.com/insights/research/how-generative-ai-enables-corporate-esg-reporting
  8. G&A Institute. (2025). Generative AI in ESG reporting: Do benefits outweigh the costs? Governance and Accountability Institute. https://ga-institute.com
  9. Gupta, R., Nair, K., Mishra, M., Ibrahim, B., & Bhardwaj, S. (2024). Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda. International Journal of Information Management Data Insights, 4(1), 100232. https://doi.org/10.1016/j.ijimei.2024.100232
  10. Hachoumi, N., Eddabbah, M., & El Adib, A. R. (2023). Health sciences lifelong learning and professional development in the era of artificial intelligence. International Journal of Medical Informatics, 178, 105171. https://doi.org/10.1016/j.ijmedinf.2023.105171
  11. Hitachi Data Systems. (2026). Artificial intelligence in ESG reporting: Transforming compliance into strategic sustainability. https://www.hitachids.com/insight/artificial-intelligence-in-egs-reporting-transforming-compliance-into-strategic-sustainability/
  12. Kharola, D. M., Goyal, M. S., & Saxena, D. S. (2025). Mandatory ESG reporting in India: Legal obligations and management strategies. Journal of Marketing and Social Research, 2(2), 167-177. https://jmsr-online.com/article/mandatory-egs-reporting-in-india-legal-obligations-and-management-strategies-63/
  13. Li, S., Younas, M. W., Maqsood, U. S., & Zahid, R. M. (2024). Impact of AI adoption on ESG performance: Evidence from Chinese firms. Energy and Environment. https://doi.org/10.1177/0958305X241269041
  14. Market.us. (2024). AI in ESG and sustainability market size, share and forecasts to 2034. Market.us Research.
  15. OMFIF. (2024). AI is driving ESG integration in emerging markets. Official Monetary and Financial Institutions Forum. https://www.omfif.org/2024/08/ai-is-driving-egs-integration-in-emerging-markets/
  16. Ray, P. (2025). BRSR reporting in India: A new paradigm. Advances in Consumer Research, 2(4), 1669-1680.
  17. Rehman, M. U., et al. (2025). Sustainable environmental monitoring: Multistage fusion algorithm for remotely sensed underwater super-resolution image enhancement and classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS
  18. Seneca ESG. (2025). India's BRSR: Strengthening ESG reporting and value chain accountability. https://senecaeg.com/insights/indias-brsr-strengthening-egs-reporting-and-value-chain-accountability/
  19. Wu, J. Y., Nataraj, V., & Day, M. Y. (2025). Generative AI in ESG reporting: A systematic review. In Sustainable Smart Cities: Intelligence, Resilience, and Equity (pp. 285-298). Springer. https://doi.org/10.1007/978-3-031-85386-9_24
  20. Zaid, M., & Issa, A. (2023). A roadmap for triggering the convergence of global ESG disclosure standards: Lessons from the IFRS Foundation and stakeholder engagement. Corporate Governance (Bingley), 23(7), 1648-1669. https://doi.org/10.1108/CG-09-2022-0399