Bayard Rezos, senior sustainability consultant at Emperor, explores how AI is rapidly becoming an essential tool for navigating the growing complexity of sustainability reporting.

In 2024, sustainability-related disclosures expanded to cover 91% of listed companies by global market capitalisation. With stakeholder expectations rising and regulations coming into effect, there’s a growing mountain of data to get to grips with. It’s no surprise that many businesses are turning towards digital tools to help them scale the terrain. 

How AI can ease the gradient 

The use of AI in sustainability reporting almost tripled in 2025 to 28%, from 11% last year2. There’s a myriad of avenues where AI can support organisations to lighten the reporting load through greater automation, enhanced accuracy, and deeper insight. 

One of AI’s biggest advantages is its processing power. With advanced analytics and machine learning, organisations can see across their entire value chain – not once a year in a static report, but in real time. The result? Clearer insights, better decisions, and greater transparency. 

AI can also help organisations tailor content for different audiences, whether that’s investors focused on risk, regulators seeking compliance, customers looking for impact or employees searching for purpose. More relevant, accessible insights build stronger engagement and deeper trust. 

Finally, AI helps reduce reporting errors by automating data validation and ensuring information is consistent. That means fewer manual errors, more reliable disclosures and better alignment with evolving standards and frameworks.   

The pitfalls (and how to avoid them) 

Like any powerful tool, AI must be used with care. To be effective, it needs to be thoughtfully integrated and grounded in your organisation’s values – otherwise, there’s a risk that it leads you off course. 

1. Smarter humans for greener algorithms

Global AI training and use is expected to account for around 4.2-6.6bn cubic metrics of water withdrawal by 2027, more than Denmark’s total annual water withdrawal. We need to balance the environmental costs against the benefits. For reporting, training your teams on the smart use of AI tools and carefully managing access can reduce the impact of using AI, while still getting maximum value.   

2. Tackle the bias before it scales 

AI systems learn from the data they’re given, and if that data reflects biases or errors, their outputs will too. Without strong oversight, AI can misrepresent information, reinforce inequalities and make misleading conclusions – creating a range of greenwashing and other reputational risks. It’s vital that your reporting systems establish clear governance, review and sign-off procedures. Equally, you should disclose how AI is being used in your reporting, including data sources, methodologies, and limitations. Being completely transparent and accountable is essential for building stakeholder confidence and minimising risk.  

3. The importance of telling a story 

Lastly, there’s a risk that we sacrifice authenticity and lose our audience. Great sustainability reporting isn’t just about data: it’s about purpose, ambition and human storytelling – the why behind the work. If you rely too much on automation, the narrative can get flattened and the emotional connection can get lost. The best reports balance data-driven disclosures with storytelling that connects stakeholders to the issues that matter most to them.  

The view from the top 

AI is already reshaping how organisations operate; sustainability reporting is no exception. Used responsibly and effectively, it will turn the disclosure mountain into a molehill. However, there is still no replacing human emotion and insight. Think brain-bot-brain in reporting; it shouldn’t be either-or. We need to use AI alongside human intellect and awareness to minimise our environmental impact, avoid reporting bias and errors, as well as engage stakeholders on the issues that matter.