As sustainability reporting becomes more demanding, companies face significant challenges in gathering, organising, and producing reports.
The European Sustainability Reporting Standards (ESRS) set out detailed requirements that can be laborious and time-intensive. However, artificial intelligence (AI) technology is offering companies a way to streamline these processes, potentially cutting compliance time by up to 50%.
Position Green, which offers a unified platform for all ESG management needs, recently explored how AI can help to cut ESRS reporting time in half.
The ESRS framework mandates organisations to report on various sustainability metrics. These range from quantitative data, such as energy consumption and emissions, to qualitative insights about governance practices and employee welfare. For large companies, collecting and compiling data, aligning it with ESRS standards, and producing comprehensive reports can take several months.
The traditional ESRS reporting process includes several key stages: data collection, mapping data to ESRS standards, structuring reports, quality assurance, and ensuring ongoing compliance. Each stage typically requires intensive manual work, often involving specialised teams dedicated to data gathering, validation, and report preparation.
AI technology has the potential to streamline each of these steps in the ESRS reporting process. Here’s how AI tools can simplify these tasks and significantly reduce the time spent on compliance:
- Automated Data Collection
Traditional ESRS reporting systems require teams to manually retrieve data from various departments. This involves contacting multiple stakeholders, gathering information from different sources, and ensuring it remains up to date. AI tools can automate much of this process by extracting data from internal systems, external databases, and unstructured documents like emails and reports. Companies can see up to 50% savings in data collection time through automated AI solutions. - Data Mapping and Policy Interpretation
Mapping data to ESRS standards involves interpreting internal policies to ensure alignment with regulatory requirements. With AI, large language models (LLMs) can automatically map policies to ESRS standards. Natural language processing (NLP) algorithms interpret and flag relevant information, enabling teams to answer compliance questions quickly. This can reduce data mapping time by 60%. - AI-Enhanced Report Generation
Producing a detailed ESRS-compliant report often requires weeks of drafting and revising. With AI, companies can generate a first draft based on collected data, maintaining consistency across narratives and improving compliance. This AI-driven approach can save up to 70% of the time typically spent on report generation, with human involvement focused on final reviews. - Quality Assurance and Data Validation
Verifying the accuracy and consistency of ESRS reports traditionally involves multiple layers of manual checks. AI models can automate these validation steps, ensuring numerical data aligns with narratives and flagging inconsistencies. AI-based validation reduces the time spent on quality assurance by up to 50%. - Real-Time Compliance Monitoring
As ESRS standards continue to evolve, companies need to stay compliant with the latest requirements. AI tools can monitor regulatory changes in real time, alerting companies to updates and recommending report adjustments. This proactive monitoring can reduce the manual effort in compliance tracking by 70%.
Industry estimates suggest that AI can reduce the overall time spent on ESRS reporting by 30-50%. These time savings not only allow organisations to focus on driving sustainability efforts but also bring other advantages:
- Enhanced Accuracy: AI models minimise human error, improving data and narrative accuracy.
- Deeper Insights: AI tools can offer real-time insights, helping companies make informed decisions that drive sustainability outcomes.
- Consistent Reporting: AI-generated reports maintain a consistent tone and structure, even when multiple contributors are involved.
Position Green, is supporting the use of AI in sustainability reporting. Its AI Analyst feature, part of the Sustainability Suite, enables companies to cut down on manual analysis and achieve a data-driven understanding of their sustainability performance. This tool helps users respond to stakeholder questions quickly and provides actionable insights, ensuring the whole organisation benefits from the sustainable goals.
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