{"id":90606,"date":"2026-04-24T10:52:24","date_gmt":"2026-04-24T08:52:24","guid":{"rendered":"https:\/\/www.gresb.com\/?page_id=90606"},"modified":"2026-07-16T11:23:55","modified_gmt":"2026-07-16T09:23:55","slug":"gresb-responsible-use-of-artificial-intelligence","status":"publish","type":"page","link":"https:\/\/www.gresb.com\/gresb-responsible-use-of-artificial-intelligence\/","title":{"rendered":"GRESB\u00a0Responsible Use\u00a0of\u00a0Artificial\u00a0Intelligence"},"content":{"rendered":"\n
\n
\n
\n\n\n \n
\n
\n \n \n
\n

As digital technologies evolve, GRESB has integrated Artificial Intelligence (AI) tools in a responsible and controlled manner to enhance efficiency, consistency, and scalability across a range of activities, including data analysis to support insight generation, analytical workflows, and operational processes. AI is used to support human expertise and decision-making rather than replace it.<\/p>\n

This statement outlines how GRESB applies AI, the principles guiding its use, and the safeguards in place to protect participant data and ensure fairness.<\/p>\n <\/div>\n \n \n

\n \n \n <\/div>\n\n \n \n <\/div>\n <\/div>\n \n <\/div>\n <\/div>\n <\/section>\n\n\n\n\n
\n
\n
\n\n\n \n
\n
\n \n

\n Our Guiding Principles For Responsible AI Use <\/h2>\n \n
\n

Transparency and accountability<\/strong><\/p>\n

At present, AI outputs are advisory and supplemental to human judgment and do not replace existing processes. Human oversight remains embedded in workflows across GRESB products and operations. As AI capabilities evolve, GRESB will continue to evaluate the appropriate balance between automation and expert review, ensuring that quality, fairness, and assurance standards are maintained.<\/p>\n

Human oversight<\/strong><\/p>\n

AI tools may assist GRESB teams in tasks such as extracting, classifying, translating, and summarizing information, identifying patterns in datasets, or supporting internal analytical workflows, including within validation processes. This includes assisting in the review of participant-submitted evidence and generating high-confidence acceptance recommendations for straightforward data points. This enables human reviewers to focus more time on edge cases and gray areas and supports consistency across decisions, assets, and managers.<\/p>\n

AI tools do not have the authority or system permissions to take actions that lead to point deductions that could reduce a participant\u2019s score without human review and approval. Any AI-supported output that could negatively affect a participant\u2019s score (including rejections or point deductions) is reviewed by qualified human reviewers, including GRESB\u2019s assurance partner (SAS) where applicable, before a decision is finalized.<\/p>\n

In addition, GRESB performs ongoing quality control over AI-supported acceptance outcomes, including reviewing a portion of high-confidence acceptance cases through sampling and targeted spot checks, to validate accuracy and continuously improve controls and guidance.<\/p>\n

Purpose-driven application<\/strong><\/p>\n

The application of AI tools focuses on areas where they can demonstrably enhance efficiency, consistency, or linguistic accuracy within the relevant operational or product processes. Examples include language translation and automated relevant text extraction and summarization to support reviewers\u2019 understanding of participant-submitted evidence.<\/p>\n

Data protection and security<\/strong><\/p>\n

GRESB enters into contractual agreements with AI service providers to ensure appropriate data protection, confidentiality, and information security safeguards consistent with its internal data governance policies.<\/p>\n

All data processed through AI systems remains protected under GRESB\u2019s data governance policies and terms and conditions. For language translation, GRESB uses the Google Translate API, which ensures that data is transmitted securely and is not retained for model training. For large language model (LLM)-based processing, GRESB uses providers with published data governance commitments (e.g., OpenAI\u2019s API and Gemini for Google Cloud). These providers state that prompts and outputs submitted via their business\/API services are not used to train models by default (unless an organization explicitly opts in), and they describe retention and security controls applicable to the service. GRESB does not opt in to having its data used for training purposes.<\/p>\n

Continuous evaluation<\/strong><\/p>\n

Given the rapid pace of technological development, GRESB regularly reviews AI-enabled processes to ensure they remain reliable, ethical, and aligned with its data-quality objectives. Any new AI deployment undergoes internal review before integration into workflows across GRESB products and operations.<\/p>\n

 <\/p>\n

Through these principles, GRESB ensures that AI strengthens, rather than replaces, the integrity and consistency of its products and operational processes, helping to deliver fair, high-quality benchmarks to the market. GRESB monitors relevant regulatory developments, including the EU Artificial Intelligence Act and applicable ESG ratings regulations. GRESB\u2019s governance framework and public disclosures will evolve as necessary to remain aligned with legal and industry standards.<\/p>\n <\/div>\n \n \n

\n \n \n <\/div>\n\n \n \n <\/div>\n <\/div>\n \n <\/div>\n <\/div>\n <\/section>\n\n\n\n\n \n
\n
\n\n

FAQ: GRESB\u2019s Use of AI <\/h2>\n \n
    \n \n
  • \n