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AI + ISSB = AISSB

Published on June 3, 2025 - In Blog Posts

By Boris Couteaux, Principal, ESG Global Advisors

AI meets ESG: Why Governance Matters More Than Ever

​Artificial Intelligence (AI) is rapidly emerging as a force multiplier for organizations across their sustainability strategy, particularly in today’s challenging economic landscape. From automating data collection and modeling climate risks to drafting entire ESG reports (as demonstrated by Google’s 2024 Sustainability Report), AI is enabling organizations to meet growing demands for transparency and performance with greater efficiency.

However, as with any powerful technology, the integration of AI into sustainability work warrants scrutiny. Sustainability professionals must recognize not only AI’s transformative potential to streamline and enhance their work, but also the significant energy demands of the new technology and the new responsibilities it brings for ESG governance. Indeed, strong governance is essential for managing the risks and opportunities associated with all ESG issues, and AI is no exception.

In this context, the foundational principles of ESG governance are being put to the test.

The Promise and the Pitfalls of AI in ESG

Across sectors, sustainability teams are beginning to integrate AI into core processes:

  • Natural & large language models (like ChatGPT) are summarizing ESG data and drafting disclosures, helping assess public and stakeholder perception and sentiment, benchmarking, disclosure mapping, audit preparation, etc.
  • Machine learning SaaS platforms are being used to predict physical climate risks for company assets or across supply chains, build scenario analysis, etc.
  • Generative tools are estimating emissions where primary data is lacking and helping calculate environmental impact of products through life-cycle-analysis (LCA)

These tools offer real gains in speed, scalability, and analytical power. But they also introduce new and underappreciated risks:

  • Opaque outputs: How do we explain the basis of an AI-driven conclusion in a disclosure?
  • Data quality issues: What happens when AI is trained on outdated, biased, or irrelevant sources?
  • Lack of auditability: Can we trace how ESG figures were produced, and are they verifiable?
  • Reputational risks: Without human intervention and guidance, AI output can often lack nuance and pose reputational risks.

In a world increasingly skeptical of greenwashing, an AI-enabled shortcut could quickly become a reputational liability.

Enter ISSB: A Governance Lens for AI Use in ESG

While AI is not explicitly referenced in the International Sustainability Standards Board (ISSB)’s S1 and S2 standards, the connection is clear. The ISSB requires companies to meet the same level of rigor, integrity, and accountability in their sustainability disclosures as in financial reporting.

Key areas where AI intersects with ISSB expectations:

1. Governance Disclosure (IFRS S1, Governance)

Organizations should describe the “governance processes, controls and procedures used to monitor sustainability-related risks and opportunities”. That includes, if applicable:

  • Oversight of third-party ESG data providers (including AI tools)
  • Internal policies governing the use of advanced technologies
  • Risk management processes linked to AI-generated outputs

If AI is influencing ESG decisions or reporting, it should be governed accordingly and in line with ISSB standards.

2. Data Quality and Verifiability (IFRS S1, Verifiability)

ISSB emphasizes that disclosures should be:

  • Accurate and free from material misstatement
  • Comparable across periods and with peers
  • Verifiable with underlying assumptions and sources

Therefore, if AI models are used to produce sustainability metrics or risk assessments, organizations should demonstrate how those outputs were validated and be able to provide an audit trail.

This is especially important as assurance expectations grow. The International Auditing and Assurance Standards Board (IAASB) is currently finalizing a new global standard — the ISSA 5000[1] — designed to guide the assurance of sustainability-related information. Expected to be implemented in some jurisdictions by the end of 2026, this framework will provide a consistent benchmark for auditors and assurance providers, supporting the credibility of disclosures made under the ISSB and other frameworks.

3. Materiality Determinations (IFRS S1, Materiality)

AI tools may influence what is deemed material – for example, by scanning news sentiment or predicting future ESG controversies. While helpful, these tools should not override human judgment or replace robust stakeholder engagement processes. Ultimately, directors and executives remain accountable for determining what is material to enterprise value.

What This Means for Canadian Companies

With the Canadian Sustainability Standards Board (CSSB) adopting ISSB-aligned standards, Canadian companies should now prepare to include AI governance in their sustainability strategies. This is especially important for firms that:

  • Use AI to generate any part of their ESG disclosures
  • Depend on third-party tools that use AI under the hood
  • Intend to report voluntarily under ISSB/CSSB frameworks

A good starting point would be to:

  • Develop or update internal AI governance policies, ideally in collaboration with IT, risk, and legal teams
  • Ensure any ESG-related AI use is auditable, explainable, and documented
  • Treat ESG data governance as seriously as financial data governance

Regulation is Coming

On top of voluntary reporting frameworks, companies should also consider binding regulation emerging globally – most notably the EU AI Act, adopted in 2024 and set to begin enforcement in stages from 2025 onward. The Act introduces a risk-based approach to AI systems, imposing strict obligations on “high-risk” applications – including those used in critical infrastructure, decision-making, and potentially in ESG reporting contexts.

For Canadian companies operating in the EU or using AI tools developed or deployed in the EU, compliance with the AI Act will require:

  • Transparency about how AI models work
  • Robust documentation and data governance practices
  • Risk assessment and mitigation procedures, particularly where AI is used in decisions that affect people or the environment

Bottom line: AI use in ESG reporting may not just need to be well-governed – it may soon be tightly regulated.

The Road Ahead: Lead with Governance, Not Hype

AI will undoubtedly reshape how sustainability is practiced and reported. But its use must be anchored in high quality governance, not just convenience or efficiency.

Companies that take shortcuts may risk credibility, investor trust, and even regulatory consequences in the near future. Those who embed responsible AI use into their ESG and risk governance systems, on the other hand, will position themselves as forward-thinking, transparent, and resilient.

Contact us to learn more about ESG Global Advisors, our team, and how we can help you with your approach to reporting under the CSRD. ESG Global offers a comprehensive range of ESG services for companies and investors. Visit Our Services to learn more.

Disclaimer: AI contributed to the creation of this article, but it was guided, reviewed and fact-checked by ESG Global’s human experts. Please note that the content and material provided in this article is for general information purposes only. It is not to be taken or relied upon as legal advice and should not be used for professional or commercial purposes. This article is intended to communicate general information about relevant sustainability matters and reporting requirements as of the indicated date. The content is subject to change based on evolving regulatory reporting requirements.

[1] International Auditing and Assurance Standards Board. (n.d.). Understanding International Standard on Sustainability Assurance 5000. https://www.iaasb.org/focus-areas/understanding-international-standard-sustainability-assurance-5000