Generative AI is revolutionizing ESG reporting, bringing efficiency and accuracy to the process. However, there are concerns about whether AI will ultimately help or hurt the corporate disclosure environment. The challenges surrounding ESG reporting, including the lack of standardization and consistent metrics, present obstacles for both investors and companies.
Investors are increasingly demanding transparency and data on how companies are utilizing generative AI. It is essential that information about AI implementation comes directly from the companies themselves, as assessments cannot be based on assumptions or potentially inaccurate information.
The emergence of machine learning and generative AI offers solutions to the challenges of data collection and reporting. Just as AI can pull real-time data on greenhouse gas emissions and identify anomalies and areas for review, it can do the same for ESG reporting. This results in significant time and effort savings across various functions.
However, it is unlikely that AI will completely replace the need for people with ESG expertise. Human input is still necessary to review and audit analysis, insights, and findings. AI simply streamlines manual work and complements the expertise of individuals.
Corporate reporting remains a headache for many companies and investors due to the lack of consensus on disclosure standards and metrics. The fragmented nature of ESG reporting frameworks compounds the issue further. Seneca ESG, a company tackling this challenge, is using large language models (LLMs) to build an AI-powered ESG assistant. This assistant incorporates a similarity score for questions across different frameworks, improving efficiency and accuracy in corporate ESG reporting.
Prompt engineering is another approach that Seneca is leveraging to optimize the AI-powered ESG assistant. By phrasing questions effectively, users can achieve the most accurate and relevant output. Seneca is testing generative AI approaches to determine the best prompts that produce optimal results based on experienced practitioners and thought leaders in corporate ESG reporting.
Generative AI presents powerful opportunities for addressing ESG challenges in corporate reporting. While progress may be slower in the short term due to the lack of clarity and consistency in AI reporting and ESG disclosure standards, once standards are clarified, generative AI can integrate ESG reporting with financial reporting. This integration will pave the way for a future in which ESG is seamlessly integrated into business operations.
In conclusion, generative AI has the potential to transform ESG reporting, streamlining data collection and analysis. However, human expertise remains vital in reviewing and auditing findings. Companies like Seneca ESG are leveraging AI to improve efficiency and accuracy in ESG reporting. Although challenges persist, the integration of ESG reporting with financial reporting is an achievable goal with generative AI.
