This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects. 

The problem

The project addresses a critical and growing challenge in the corporate world: the complex and time-consuming process of creating climate financial disclosure reports. As global awareness of climate change’s impacts increases, so does the demand for businesses to transparently report their environmental footprint and sustainability practices. This demand is encapsulated in frameworks like the IFRS S2 and ESRS E1, which set out detailed requirements for climate-related financial disclosures. However, the process of compiling these reports is fraught with challenges. It requires gathering vast amounts of data, analyzing it to extract meaningful insights, and then presenting these in a format that meets regulatory standards. This not only demands significant manual effort but also poses a high risk of inaccuracies, which can lead to non-compliance and potential reputational damage.

The impact of these challenges is multifaceted. For businesses, the manual and labor-intensive process of report generation diverts resources away from core activities, impacting operational efficiency. The complexity of compliance requirements also means that businesses often struggle to ensure their reports are comprehensive and fully aligned with regulatory standards, risking penalties and loss of investor confidence. Moreover, inaccuracies in these reports can mislead stakeholders about a company’s environmental impact and sustainability practices, undermining efforts to promote transparency and accountability in corporate environmental performance.

Furthermore, the broader push towards sustainable business practices is hampered by the current inefficiencies in climate disclosure reporting. Without the ability to efficiently report on sustainability metrics, businesses may be less inclined to adopt greener practices or invest in reducing their environmental footprint. This not only affects individual companies but also hinders broader societal efforts to combat climate change through enhanced corporate responsibility.

By automating the creation of climate financial disclosure reports with AI and large language models (LLMs), the project aims to address these challenges head-on. The initiative seeks to streamline the reporting process, significantly reducing manual effort, improving accuracy, and ensuring that reports meet the comprehensive requirements of regulatory frameworks. This automation is crucial for enabling businesses to efficiently meet regulatory demands, thereby facilitating greater transparency in corporate sustainability practices and contributing to the global fight against climate change.

The project goals

The primary aim of this project is to enhance sustainable business practices by developing an AI-powered tool for automating climate disclosure reporting, aligning with the IFRS S2 and ESRS E1 frameworks. This initiative is essential for enabling businesses to efficiently meet regulatory requirements, leveraging AI and large language models (LLMs) to streamline the generation of report drafts. The project will be in the following planned phases:

• Development of AI Algorithms: The project will focus on creating AI algorithms capable of analyzing both customer and publicly available data.
• Prototype Development: The initial goal is to develop a prototype demonstrating the core functionality of the AI-driven report generation process. This includes stages of data ingestion, analysis, report drafting, and basic editing capabilities, providing a tangible proof of concept for the tool’s potential.
• Data Sources Integration: The system will leverage data from different sources, encompassing quantitative and qualitative climate risk and opportunity data, and External Public Data, utilizing APIs from financial and environmental databases for auto-filling company-specific information.
• Report Generation Mechanisms: The project will enable the generation of editable reports in PDF and Word formats, respectively. 
• User Interface Development: A basic UI will be developed for internal stakeholders to test the system’s core functionalities. 
• Feedback Loop Establishment: An iterative feedback loop with internal stakeholders for identifying and addressing any issues early on, ensuring the tool’s effectiveness and user satisfaction.

Thus, the project aims to deliver a Minimum Viable Product that showcases the capabilities of the AI-powered climate disclosure reporting tool and lays the groundwork for further advancements. This project is set to significantly impact how businesses approach sustainability reporting, providing a dynamic, accurate, and user-friendly method for generating climate disclosure reports, thereby contributing to more sustainable business practices.

**More details will be shared with the designated team.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works