With increasing requirements around sustainability reporting, such as CSRD legislation, the manufacturing industry faces a major challenge. How do you ensure that existing sustainability standards, such as Cradle to Cradle®, align with the expanded ESRS requirements?
Together with a consulting firm active in circular innovation, we developed a smart, future-proof AI solution that helps companies streamline this complex process. By harnessing the power of generative AI, we were able to effectively connect data, accelerate insights and lay a solid foundation for more efficient sustainability reporting.
Industry: Consulting firm for circular innovation
Location: Eindhoven
The challenge
With the advent of mandatory CSRD legislation, this organization faced a challenge: how to translate existing sustainability guidelines, such as from Cradle to Cradle® (C2C) , into mandatory ESRS reporting? The ESRS guidelines include as many as 1167 data points, so companies quickly become overwhelmed. There is overlap between the two standards, but there are also differences. Complex matter that is very labor-intensive to keep up with due to rapid changes.
Together with our client, a knowledge partner for circular innovation, we sought a solution for the manufacturing industry to effectively link existing Cradle-2-Cradle certification data to CSRD/ESRS reporting guidelines.
The following question was posed to Beeminds’ experts:
“How can all the new AI & ChatGPT innovations help us simplify this complex and time-consuming process?”
Our approach: GenAI as a smart sustainability specialist
Beeminds developed a Copilot in collaboration with a leading sustainability specialist. The project focused on analyzing the overlap between the Cradle to Cradle Certified® standard and the ESRS standards. Using state-of-the-art AI technology, such as Microsoft Azure OpenAI Services, we conducted a thorough comparison, within the client’s environment.
The approach consisted of:
- Smart analytics with AI
Using a Large Language Model (LLM), we had ChatGPT fathom the complexity of the standards and thus understand the overlap. - Iterative sprints
In four phases, we analyzed the similarities and differences between the standards and made the AI model a little bit better each time. - Validation by experts
The AI results were continuously verified by sustainability specialists to ensure accuracy.
The results
During this project, we delivered the following results:
- Summary analyses
The AI was able to identify both explicit and implicit similarities between standards, leading to deeper insights. For each similarity, substantiation was provided by the model. - Reliable validation
Experts confirmed that the AI models produced consistent and accurate results. In some cases, the AI model even established a relationship that even surprised the experts. - Future-proof
The solution uses publicly available information from PDF files and can be easily updated as sustainability guidelines change. - Efficiency
Thanks to modern AI technology in the Microsoft cloud, we were able to save significant time and costs. The infrastructure cost of the project was less than €100.
“An audit conducted by one of our sustainability specialists showed that the AI assistant got it right in almost all cases. The relationships established by the model are at least impressive and in a number of cases even provided us and our clients with renewed insights.”
Senior Real Estate Consultant
Key learning points
Valuable learning points also emerged during the project:
- Small & focused questions work better
The model produces the best results when the assignment is specific, such as analyzing a particular paragraph within a standard. In addition, breaking up complex problems works best. - Context is crucial
Company-specific data must be provided in a structured manner to be useful for AI modeling. This can be passed on prior to conducting the analysis. - Use current data
Working with the most recent and complete versions of sustainability standards is essential for accurate analyses.
“Working with Beeminds and using advanced AI technology has given us valuable insights into how to achieve our sustainability goals. The results of this project show that AI can play a crucial role in accelerating sustainable transitions.”
Senior Real Estate Consultant
Technology for sustainable reporting
Beeminds used Microsoft Copilot Studio and Azure OpenAI Services to develop a secure and scalable AI solution. This technology allows the power of ChatGPT to be leveraged within a private cloud environment without compromising privacy or security. Thanks to the pay-per-use model, costs remain low while value is high.
Why AI is a game changer for sustainability
This innovative application shows that AI can play a crucial role in the sustainable transition of companies. Linking existing sustainability data to new mandatory reporting standards not only simplifies the process but also maximizes the environmental impact. We are making a virtue out of a necessity.
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