Latest update September 15, 2025
[cg_add-class=heading-style-h4]In a Nutshell
- ESG, EHS, and QM teams spend a large part of their time on recurring questionnaires from EcoVadis, CDP, customers, or auditors.
- Much of the content overlaps: emissions data, climate targets, supply chain guidelines, social standards, and evidence are requested multiple times.
- Scattered data and unclear responsibilities lead to duplication of work, inconsistencies, and time pressure.
- With a collaborative AI platform, answers, key figures, and documents can be centrally bundled and reused multiple times.
- Sunhat's collaborative proof platform suggests appropriate answers, automatically links evidence, and ensures consistent results across all departments.
Whether sustainability, ESG, EHS, or quality management – questionnaires are becoming increasingly important in all areas. Companies respond to requests from EcoVadis, CDP, customers, investors, or auditors on an almost daily basis. The content overlaps significantly, but differs in detail. For the teams responsible, this means many hours of additional work and a high level of coordination.
ESG Questionnaires: The Same Topics in Different Formats
Many requirements are similar. Emissions data is requested by various parties alike. Climate targets, reduction strategies, and roadmaps are just as much in demand as policies on suppliers or risk analyses in purchasing. Social issues such as employee rights, diversity, or health and safety also appear in almost every questionnaire. In the end, companies also have to submit evidence and certificates that they have often already submitted multiple times.
For sustainability teams, EHS managers, or quality managers, this means that identical information has to be compiled again and again, often only because the wording and requests differ.
The Biggest Challenges with ESG, EHS, and QM Questionnaires
However, the real difficulty here lies not in the complexity of the questions, but in the internal process. Data is often stored in different systems, answers are reformulated from year to year, responsibilities are sometimes unclear, and tight deadlines put additional pressure on teams.
Frequently occurring problems include:
- Scattered data sources that are difficult to keep track of
- Duplicate work because answers are created multiple times
- Unclear responsibilities for data delivery and approval
- Inconsistencies in wording
This can quickly lead to delays or quality problems, especially in the case of ratings or customer inquiries. Even minor inconsistencies can undermine stakeholder confidence and weaken competitiveness.
Leveraging Synergies with a Collaborative AI Platform
A collaborative AI platform such as Sunhat provides a solution here. Instead of each department working independently, approved, collaboratively created responses, data, and evidence are bundled centrally. Unlike simple filing or SharePoint solutions, the information in Sunhat is audit-ready, consistent, and reusable at any time.
This offers several advantages:
- Emissions data or policies can be maintained once and used multiple times.
- Standard responses are available as reusable text modules.
- Approved documents and certificates are stored centrally and can be accessed at any time.
- All departments access the same database, which increases consistency and quality.
This saves valuable time not only for sustainability teams, but also for EHS, sales, and QM departments that regularly have to answer questionnaires.
AI as an Accelerator in the Response Process
AI makes the entire process more efficient and also improves the quality of results by reducing manual intervention. Platforms such as Sunhat recognize recurring questions, compare them with existing content, and suggest appropriate answers. Documents and evidence are automatically linked, eliminating the need for lengthy searches.
The advantages are obvious: less manual effort, consistent answers across departments, lower risk of errors, and significantly more freedom for strategic work.

Conclusion: Less Effort, More Impact
Questionnaires and ratings are not going to disappear – on the contrary, they will increase. Companies that centralize data and use modern technologies will gain a valuable advantage here if they already rely on an AI-supported solution.
Optimize data processes and save time
While ESG questionnaires primarily focus on sustainability, climate targets, and social responsibility, EHS questionnaires focus more on occupational safety, environmental management, and health. QM questionnaires, on the other hand, often relate to certifications and quality standards. In practice, however, the requirements overlap significantly – much of the data and evidence can be used multiple times.
Recurring topics include emissions data (Scope 1-3), climate targets, emission reduction strategies, supply chain guidelines, social standards, and evidence such as certificates or policies. Companies that collect this content centrally can reuse it efficiently in various questionnaires and ratings.
The key lies in centralizing and reusing information. An enterprise response layer bundles data and evidence so that teams don't have to start from scratch every time. AI-powered software can also automatically analyze questionnaires and suggest appropriate answers, significantly reducing the processing effort.