How ESG and AI are reshaping board meetings

Conversations around ESG have become more complex. The same is true of the tools used to support them. Artificial intelligence is now part of how organisations collect ESG data, report on progress, and flag potential risks. As a result, boards are seeing the effects in their meetings, from the information presented to the decisions expected. 

When AI influences how ESG data is gathered and explained, boards need to know where it fits, what it changes, and what could go wrong. That means knowing which questions to ask, and how to make room for them on the agenda, rather than learning how the technology works. 

As Nick Ashford from ESG Advisors explains, “Boards that treat AI as a strategic ESG issue, not just a technology tool, will be better positioned to unlock its value while safeguarding reputational and ESG risks. Governance must evolve to match its scale and speed.” 

This article explores: 

• How ESG and AI are converging at board level 
• What responsibilities boards have in ESG and AI
• The questions boards should ask when it comes to ESG and AI
• How to optimise board meetings to support successful oversight

How AI is influencing ESG discussions in the boardroom 

AI is starting to shape what boards see, and what they don’t, when reviewing ESG performance. It’s already being used to extract data from reports, track progress on emissions targets, monitor supply chain activity, and summarise regulatory developments. These outputs often appear in meeting materials with little visibility into how they were produced. 

This can raise problems. If board members aren’t aware that data has been selected or interpreted by AI, they may assume it’s been reviewed by people. And if the board doesn’t know which systems are being used, or how much they influence what’s presented, it’s harder to judge what questions need asking. 

AI also has the potential to improve ESG oversight. When used well, it can reduce the time spent compiling reports and increase the time available for strategic discussion. But that benefit only holds if the board is confident in the process behind the data. 

What responsibilities do boards have in ESG and AI? 

Boards are expected to review ESG strategy and performance. That hasn’t changed. What has changed is how that information is being produced. More and more, it’s shaped by AI tools before it reaches the boardroom. As explained in PwC’s annual Corporate Directors Survey, “The board’s role, as with any significant strategic initiative, is to provide oversight and guidance to management. Typically, the full board should be involved in overseeing the company’s AI business transformation given its strategic and risk implications.” 

This matters when directors are asked to sign off on reports, assess progress, or make decisions that rely on data. If AI has played a role in preparing that data, it’s reasonable to ask how it was used, and whether it introduces any blind spots. 

There are a few places where this comes up: 

1. In meeting materials: If AI has influenced what’s being presented, boards should be made aware of that during preparation. 

2. In committee discussions: Audit and risk committees may need to check whether reporting and assurance processes still hold up as new tools are introduced.

3. In policies and disclosures: ESG frameworks may need to be revisited if the systems used to implement them have changed. 

The board isn’t there to review technical systems, but it is responsible for ensuring that information used in meetings is clear, reliable, and complete. 

Which ESG reporting risks involve AI? 

AI tools are becoming part of how ESG data is gathered and reported, but the risks they introduce aren’t always clear from the materials boards receive. 

Some data arrives without explanation 

Meeting packs often include charts, scores or summaries that have already been shaped by AI. If it’s not obvious where that data came from, or what assumptions were made in processing it, directors are left without the full context. 

Bias isn’t always visible 

AI systems can reflect the gaps in their training data. That matters when tracking metrics like diversity, supplier ethics, or environmental impact. The numbers may look neutral, but the inputs behind them may not be. 

Polished doesn’t always mean reviewed 

AI-generated insights often appear complete, even when they haven’t been checked by a human. This creates a false sense of confidence, especially when time is limited and materials are dense. 

These issues don’t require technical answers from the board. They call for practical ones: Where are we using AI? Who reviews the outputs? And how do we know what we’re seeing is accurate? 

What questions should boards ask to guide ESG and AI alignment? 

Boards are not expected to evaluate technology, but they are expected to evaluate the information presented in meetings. That includes understanding whether AI has played a role in ESG reporting, and what effect that might have on the reliability of the data. As Sung Une Lee et al explain in a recent academic study, “AI adoption should be viewed through the lens of ESG to mitigate risks, align AI with societal goals and support responsible investments.”  

A good starting point is to ask if AI tools are being used to collect or summarise ESG information. If they are, boards should understand how those tools are managed, how outputs are reviewed, and whether the process has changed since previous reporting cycles. 

It’s also important to ask about external disclosures. If ESG statements or sustainability reports are based in part on AI-generated insights, boards should know how those insights are produced and how much confidence can reasonably be placed in them. 

How should boards prepare meetings for ESG and AI oversight? 

As AI becomes part of ESG reporting, boards should be clear on where it’s being used, and how that shapes what’s brought into meetings, and many simply aren’t prepared. According to 2025 research from Deloitte, “Nearly 40 percent of boards report they are experimenting with AI, but more than 50 percent feel they should accelerate how they embed AI into their agendas if they want to more effectively oversee its adoption.”  

Where AI-generated insights are included in board packs, they should be identified early. Directors need to understand what role automation played and whether the results have been reviewed before reaching the table.   

This matters in cases where: 

1. Reports are shared externally 

2. Strategic decisions rely on ESG data 

3. Risk assessments are informed by automated systems  

Audit and risk committees may need time to review whether existing controls still cover these areas. In some cases, changes in reporting tools may require updates to assurance processes. 
 
The format of meetings doesn’t need to change. What matters is knowing when AI is involved and building in time to question what it may have missed. 

What should boards take away from all this? 

AI is already shaping how ESG data is produced, summarised, and reported. That influence will only grow. Boards don’t need to become experts in the tools, but they do need to understand when those tools affect the information they’re being asked to review. 

A few principles help keep governance on track: 

1. Be clear when AI is involved in ESG analysis or reporting 

2. Ask whether the outputs have been reviewed, and by whom 

3. Make space in meetings to question how insights were produced 

4. Ensure accountability is visible, even when the process isn’t   

ESG oversight relies on good information. When that information is shaped by AI, the board’s role is to check that nothing essential has been left out. 

If you're ready to optimise your board meetings for successful ESG and AI oversight, book a demo and find out how Sherpany can help.