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Organisations want AI to take the manual work out of sustainability reporting, but most are stuck at the same first hurdle: getting the raw data in one place. That was the clearest message from a recent roundtable we hosted at KEY ESG, the AI-powered sustainability data platform, with eight senior investment and sustainability professionals. The conversation was held under Chatham House rules, so here are the themes rather than the names, and they apply well beyond the investment community.
Key takeaways:
- Data collection, not AI capability, is the biggest barrier to using AI in sustainability reporting.
- AI is seen as a way to reduce manual work, not as a replacement for internal expertise.
- Knowing that advisors already use AI is changing how organisations think about bringing reporting in-house.
- Growing regulatory obligations make reliable, organisation-wide data collection more important than ever.
The biggest barrier to using AI in sustainability reporting is data collection. Before AI can analyse anything, the raw information has to be gathered and centralised. For larger organisations with mature ERP systems, that is manageable. For smaller businesses, subsidiaries and sites, much of the relevant data still sits in invoices, utility bills and spreadsheets.
Several attendees said the most valuable use of AI right now may be the unglamorous one: reading and structuring source documents so the data exists in the first place.
AI cannot replace internal sustainability expertise, and few expect it to. Most are enthusiastic about using AI to reduce the hours spent on manual collection, chasing and checking, but the consensus was that AI works best in the hands of people who understand the frameworks, the data and the context, and who can judge when an output does not look right.
More organisations are leaning towards bringing sustainability reporting in-house, because the reason for outsourcing it has changed. In the past, some hesitated to run sustainability reporting through software, feeling more comfortable handing it to consultants with people doing the work. That assumption is shifting. There is growing recognition that advisors are themselves using AI to gather data, run benchmarks and draft reports, so outsourcing no longer means the work is done by hand.
Once that becomes clear, the question moves from "software or people?" to "who owns the process?" Much of this work follows the same steps every cycle, which makes it well suited to a scalable, repeatable process supported by software and AI, with internal experts in control and advisors brought in where specialist judgement is genuinely needed.
Regulation raises the bar for consistent sustainability data collection across the whole organisation. Everyone at the roundtable is subject to sustainability disclosure requirements, whether under the Sustainable Finance Disclosure Regulation (SFDR), the Corporate Sustainability Reporting Directive (CSRD) or other frameworks. For groups with subsidiaries or majority-owned businesses, that means consolidating those entities into their own reporting, which makes reliable data collection across every part of the group even more important as the 2026 reporting season approaches.
The message from the room was clear. Organisations want AI that solves the data problem first, supports their own experts rather than replacing them, and turns recurring reporting work into a repeatable process they own.
How is AI used in sustainability reporting?
AI can read and structure source documents such as invoices and utility bills, flag anomalies, benchmark performance and draft disclosures. It reduces manual work while internal experts keep control of judgement and sign-off.
Can AI replace sustainability consultants?
AI can take over much of the repeatable work that has traditionally been outsourced, such as data gathering, benchmarking and first drafts. Specialist advisors still add value where complex judgement or interpretation is needed.
Can one data process support multiple reporting frameworks?
Yes. When data is collected and validated once in a central place, the same underlying information can feed several frameworks, including SFDR, CSRD, ISSB, GRI, EDCI and UK SRS.
KEY ESG is an AI-powered platform that helps private equity firms, fund managers, their portfolio companies and corporates collect, validate and report sustainability data, from reading source documents to producing reports aligned with global frameworks and regulations, including SFDR, CSRD, ISSB, GRI, EDCI, UK SRS and more.
Book a demo: https://www.keyesg.com/request-a-demo
Organisations want AI to take the manual work out of sustainability reporting, but most are stuck at the same first hurdle: getting the raw data in one place. That was the clearest message from a recent roundtable we hosted at KEY ESG, the AI-powered sustainability data platform, with eight senior investment and sustainability professionals. The conversation was held under Chatham House rules, so here are the themes rather than the names, and they apply well beyond the investment community.
Key takeaways:
- Data collection, not AI capability, is the biggest barrier to using AI in sustainability reporting.
- AI is seen as a way to reduce manual work, not as a replacement for internal expertise.
- Knowing that advisors already use AI is changing how organisations think about bringing reporting in-house.
- Growing regulatory obligations make reliable, organisation-wide data collection more important than ever.
The biggest barrier to using AI in sustainability reporting is data collection. Before AI can analyse anything, the raw information has to be gathered and centralised. For larger organisations with mature ERP systems, that is manageable. For smaller businesses, subsidiaries and sites, much of the relevant data still sits in invoices, utility bills and spreadsheets.
Several attendees said the most valuable use of AI right now may be the unglamorous one: reading and structuring source documents so the data exists in the first place.
AI cannot replace internal sustainability expertise, and few expect it to. Most are enthusiastic about using AI to reduce the hours spent on manual collection, chasing and checking, but the consensus was that AI works best in the hands of people who understand the frameworks, the data and the context, and who can judge when an output does not look right.
More organisations are leaning towards bringing sustainability reporting in-house, because the reason for outsourcing it has changed. In the past, some hesitated to run sustainability reporting through software, feeling more comfortable handing it to consultants with people doing the work. That assumption is shifting. There is growing recognition that advisors are themselves using AI to gather data, run benchmarks and draft reports, so outsourcing no longer means the work is done by hand.
Once that becomes clear, the question moves from "software or people?" to "who owns the process?" Much of this work follows the same steps every cycle, which makes it well suited to a scalable, repeatable process supported by software and AI, with internal experts in control and advisors brought in where specialist judgement is genuinely needed.
Regulation raises the bar for consistent sustainability data collection across the whole organisation. Everyone at the roundtable is subject to sustainability disclosure requirements, whether under the Sustainable Finance Disclosure Regulation (SFDR), the Corporate Sustainability Reporting Directive (CSRD) or other frameworks. For groups with subsidiaries or majority-owned businesses, that means consolidating those entities into their own reporting, which makes reliable data collection across every part of the group even more important as the 2026 reporting season approaches.
The message from the room was clear. Organisations want AI that solves the data problem first, supports their own experts rather than replacing them, and turns recurring reporting work into a repeatable process they own.
How is AI used in sustainability reporting?
AI can read and structure source documents such as invoices and utility bills, flag anomalies, benchmark performance and draft disclosures. It reduces manual work while internal experts keep control of judgement and sign-off.
Can AI replace sustainability consultants?
AI can take over much of the repeatable work that has traditionally been outsourced, such as data gathering, benchmarking and first drafts. Specialist advisors still add value where complex judgement or interpretation is needed.
Can one data process support multiple reporting frameworks?
Yes. When data is collected and validated once in a central place, the same underlying information can feed several frameworks, including SFDR, CSRD, ISSB, GRI, EDCI and UK SRS.
KEY ESG is an AI-powered platform that helps private equity firms, fund managers, their portfolio companies and corporates collect, validate and report sustainability data, from reading source documents to producing reports aligned with global frameworks and regulations, including SFDR, CSRD, ISSB, GRI, EDCI, UK SRS and more.
Book a demo: https://www.keyesg.com/request-a-demo
