Verify and Enhance AI-Assisted Sustainability Disclosure
Move fast with AI. Stay credible with our expertise.
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Expert review of AI-assisted sustainability work
AI is increasingly being used to reduce workloads and speed up sustainability reporting and questionnaire responses. We step in after that, to make sure your AI-generated content is accurate, defensible, and aligned with the standards and frameworks your stakeholders expect before it’s submitted for assurance, sent to clients, or published.
WHY DOES AI-GENERATED SUSTAINABILITY CONTENT NEED EXPERT REVIEW?
AI can reduce the workload for generating sustainability disclosures, but our clients find the output is not always reliable. G&A helps confirm every figure, claim, citation, and framework reference to best reflect your company.
Data accuracy
Catch outdated figures, mislabeled metrics, and inconsistencies before publication
Source integrity
Verify citations and quotations to ensure every source reference is accurate
Standards alignment
Ensure reporting requirements are interpreted and applied correctly
Defensible claims
Keep commitments and performance statements within evidential boundaries
Stakeholder confidence
Reduce credibility risk with investors, raters, regulators, and other stakeholders
One company’s story.
In 2025, a Big Four accounting firm was forced to partially refund a government client after an AI-assisted report it had delivered as independent, expert-checked work was found to contain fabricated academic references and a generated quote falsely attributed to a court judgment. The report was part of a contract worth roughly US$290,000. We believe that AI is a great tool, and that it needs an informed, human check before it goes out the door.
Why work with G&A
In sustainability, errors have consequences. A number that doesn’t reconcile or a claim you can’t defend can lead to a credibility or legal problems with investors, raters, and regulators.
Request a Sample Review
We get your AI-assisted work ready for the assurance process. A pre-assurance review means a clean submission, fewer surprises, and a faster process when it reaches your assurance provider.
We check sustainability claims, data, and evidence against the standards and frameworks your stakeholders expect — GRI, SASB, ISSB, ESRS, TCFD. AI tools — even the ones now built specifically for sustainability — can flag patterns and inconsistencies, but they can’t gauge whether a Scope 3 figure is actually defensible, judge whether a claim will read as overstatement, or stand behind the answer. That judgment and that accountability are what we add.
With 20 years of disclosure advisory experience and 15 years of S&P 500 / Russell 1000 research on corporate reporting practices, we know what “good” looks like.
We’ve spent two decades researching, writing, and advising on ESG disclosures for investors, raters, customers, and regulators. Our review ensures your content reads appropriately for your anticipated audiences.
How the review works
Scope the AI use: What AI was used for and who the audience is.
Collect the inputs: AI prompts, source documents, data tables, prior reports, and relevant standards and framework requirements.
Review content and evidence: Focus on accuracy, consistency, standards and framework alignment, source traceability, and communication risk.
Trace and score: Map each material claim to an approved source and classify every finding by severity and type.
Deliver and install controls: Redlines, an issue log, prioritized recommendations, and repeatable review gates for your next AI-assisted cycle.
A Deeper Dive into Our Process
Ways to engage
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AI Output Quality Check: For teams using AI casually for early drafts and summaries. A focused review of selected work product: redlines, an issue log, a source spot-check, and top remediation recommendations.
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AI-Assisted Disclosure Review: For teams using AI for reporting, disclosure, ratings responses, or investor materials. The full engagement: AI-use intake, complete work-product review, Evidence Traceability Matrix, standards and framework-alignment and claim-substantiation review, greenwashing and credibility assessment, and a final QA memo.
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Managed AI Review & Controls: For teams using AI in every reporting cycle. An ongoing engagement: recurring reviews across cycles, plus human-in-the-loop controls, an approved-use policy, and reviewer checklists — so quality holds as your team scales its AI use and the standards evolve. We maintain the review capability with you, cycle after cycle.
What a finding looks like
A single review typically surfaces dozens of findings. Here is one, anonymized:
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AI-assisted claim: “We reduced our carbon emissions by 32% since our baseline year.”
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Our review: The disclosure doesn’t contain the context this claim needs — which GHG emissions scopes it covers (1, 2, and/or 3), the baseline year, the boundary, or whether prior years were restated. In addition, the number itself was wrong in three compounding ways: the 32% was actually the reduction in electricity use, not carbon emissions; it had been carried forward from a report two years old; and the current figure was 48%.
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Risk level: High
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Our recommendation: Correct the metric and the current figure, add the scope, baseline year, and boundary, and reconcile every number against source data before publishing.
Questions and Answers
An informed, human review of sustainability content your team has produced with help from AI tools, including reports, framework mappings, ratings responses, investor and board materials. Your work is checked for accuracy, evidence, standards alignment, and credibility before it’s published or submitted.
AI accelerates many steps in sustainability reporting, but AI tools can mislabel a metric, carry a stale figure forward, invent a source, or misapply a standard. The mistakes, however important, can be hard to catch. Sustainability content carries higher stakes than generic copy and can increase your investor, regulatory, and reputational risk.
Factual accuracy, source traceability, standards and framework alignment, data consistency, claim substantiation, greenwashing risk, and whether the language is credible for investors, raters, and regulators.
GRI, SASB, ISSB / IFRS S1-S2, ESRS / CSRD, TCFD, TNFD, and stakeholder responses including CDP, S&P CSA, EcoVadis, and GRESB.
No — our review takes place before assurance to ensure your AI-assisted work is ready for the assurance provider, which makes that process faster and smoother.
Our review is human-led. Where we use AI internally to support it, client content is handled under strict confidentiality, and confidential or non-public information is never used in any way that breaches that confidentiality.
Send us a sample of the AI-assisted work you’re preparing, and we’ll scope the right level of review.
Let's start a conversation.
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