How efficient is AI-supported sustainability reporting? In our webinar, we presented specific use cases, limitations, and success factors using the VSME standard as an example.
Creating a VSME report is not a “one-prompt project.” AI only unleashes its added value in a structured, iterative process. It helps derive a VSME-compliant outline, develop a consistent chapter structure, and systematically link strategy, risks, and KPIs. A clean database is a prerequisite: AI can only work efficiently and purposefully if content is centrally bundled and clearly documented.
Text creation with quality assurance
AI also demonstrates its strengths in text creation. Content can be structured along defined VSME data points, with tone and scope controlled in a targeted manner. Standardized, recurring report content is particularly suitable. At the same time, hallucinations, inaccurate technical terms, or incorrect data transfers make technical review essential. Quality and compliance require control at every stage.
At the same time, hallucinations, inaccurate technical terms, or incorrect data transfers make technical review essential. Quality and compliance require control at every stage.
Conclusion: Efficiency through structure and expertise
The VSME report is ideal as an introduction to AI-supported reporting. Those who use AI in a structured manner and provide technical support can significantly accelerate processes – without compromising on quality and regulatory security.
Would you like to view the recording of our webinar?
Simply send us a brief email to: esg@ir-on.com
