Using AI in sustainability reporting and how it assists in ISSB disclosure

Sustainability reporting has reached a turning point. With the introduction of the International Sustainability Standards Board (ISSB), standards like IFRS S1 and S2 are revolutionising the way organisations disclose their environmental, social, and governance (ESG) performance. These standards aim to bring about global ESG reporting harmonisation and ensure sustainability information becomes as transparent and comparable as financial reports.

But for most firms, that’s not a simple thing to do. Sustainability teams are drowning in siloed data, evolving regulations, and hand-built spreadsheets. With deadlines tighter than ever and expectations higher than ever before, the challenge of assembling ESG reports is tougher than ever.

That is where AI assisted ESG reporting steps in. Artificial intelligence makes it possible now to automate data collection, improve data quality, and ensure compliance with standards like ISSB, CSRD, and GRI. For forward-thinking companies, AI is not taking over human control, it’s empowering teams to finish sustainability tasks faster, more efficiently, and more precisely.

Understanding ISSB disclosure requirements

ISSB was established to give a global foundation for sustainability reporting. Its two foundational standards, IFRS S1 (General Sustainability-related Disclosures) and IFRS S2 (Climate-related Disclosures), require companies to make disclosures of risks and opportunities that could affect enterprise value.

The aim is to be consistent. Regulators and investors are looking for ESG data that they can apply uniformly across industries and geographies. ISSB’s framework demands structured, auditable, decision-useful disclosures. That means high-quality, joined-up information from every corner of an organisation’s activities, which in the past has been challenging to provide.

ISSB is also building accountability. Every data point must be traceable and supported by evidence, so manual labor and static spreadsheets are no longer on the table. As AI sustainability reporting becomes more mature, it’s giving a bridge between sustainability ambition and the operating truth of compliance.

Why traditional ESG reporting tools fall short

Most organisations stick to legacy ESG reporting infrastructure, Excel spreadsheets, stand-alone software, or siloed sustainability platforms. Such approaches have classic pain points:

• Manual data entry of finance, HR, procurement, and operations systems.
• Regions and departments with unevenly shaped metrics.
• Difficulty mapping to ISSB, IFRS, and CSRD standards.
• Very little validation time, with room for human error.

The result? Delays, inaccuracies, and potential non-compliance. In an era where ESG information drives investment decisions, these gaps can harm reputation, impede assurance processes, and erode stakeholder confidence.

It’s why more and more companies are adopting ESG reporting automation technology. When augmented by AI, these technologies make ESG data management a continuous, forward-looking activity instead of a fire-drilled process.

How AI transforms sustainability reporting

AI is no longer just jargon in sustainability, it’s fast becoming the cornerstone of data integrity and compliance. This is how it’s changing the game for sustainability teams:

1. Data aggregation and integration

AI interfaces directly with a number of systems, including finance, HR, supply chain, environmental monitoring, and carbon accounting systems. Instead of having to manually patch together spreadsheets, it automatically pulls together, cleans, and organises information according to GHG Protocol and ISSB-aligned frameworks.

It also standardises formats and fills in gaps of information, resulting in a consistent view of an organisation’s sustainability effect. This merging creates a foundation for reliable, open reporting.

2. Data validation and accuracy

Machine learning models continuously monitor ESG data sets for inconsistencies or gaps. Should a company post energy consumption way beyond normal parameters, AI can alert it and even propose fixes based on past performance or industry comparisons. The outcome is cleaner, more accurate, and auditable data, critical to ISSB reporting.

3. Intelligent workflows

AI doesn’t simply handle data, but processes. Automated processes remind, monitor review deadlines, and ensure not to overlook crucial disclosure steps. Compliance checks throughout offer visibility for sustainability teams working through ISSB’s demands, with each report section delivered precisely and on time.

4. Smart insights and narratives

With AI-assisted ESG compliance, raw data never sits still. The AI software can write narrative sections of reports, recognise material issues, and even predict future performance trends. Such insights allow organisations to transcend mere compliance validation, turning raw ESG data into actionable intelligence for strategic planning.

How AI specifically assists with ISSB disclosure

AI’s real advantage lies in its alignment with ISSB’s core principles. They are completeness, accuracy, consistency, timeliness, and auditability. Here’s how it translates in practice:

By automating these stages, AI eliminates manual bottlenecks and helps ensure that sustainability reports stand up to scrutiny, from internal auditors to external regulators.

For example, a global retailer would use AI-powered ESG platforms to consolidate emissions data of hundreds of suppliers. The platform would validate and standardise the data against IFRS S2 standards, producing automatic reports showing climate footprint in Scope 1, 2, and 3 categories. Instead of reconciling manually for months, the whole process takes weeks with the help of auditable trail data.

Getting started with AI-enabled ESG reporting

Transitioning to AI-assisted reporting need not be daunting. The process starts with some simple steps:

1. Materiality assessment: Begin by identifying key sustainability matters with assisted AI processes. These tools can search for stakeholder expectations and regulatory relevance to prioritise what is most significant.
2. Combine your data sources: Unite finance, operations, HR, and supply chain data to create a single ESG repository. Integration offers consistency across departments and eliminates the time for repeated manual inputs.
3. Perform a gap analysis: AI software can compare your existing reporting against ISSB and IFRS S1/S2 standards, highlighting data gaps or inconsistencies before submission.
4. Automate and validate: Utilise AI to validate for anomalies, fill in missing data in a clever way, and create audit-readiness of documentation throughout the reporting cycle.
5. Act on insights: Apply predictive analytics to identify sustainability risks, compare against peers, and guide future improvement in performance.

Organisations that use these steps find that the benefits go far beyond compliance. AI-driven ESG reporting offers faster turnaround times, improved assurance readiness, and greater stakeholder confidence.

See for yourself

Would you like to see practical applications of AI in ESG reporting?

Book a 30 minute demo, and chat with an ESG data expert:

The human element in AI-driven ESG

Keep that in mind, it’s well worth remembering: automation can only be as good as the humans who build it. AI crunches the numbers, but sustainability experts inject the judgment, interpreting the insights, double-checking the outcomes, and informing strategy. AI-powered sustainability reporting is genuinely revolutionary since it combines human judgement with machine accuracy.

At Ikano Insight, our vision for this collaboration is the future of sustainability intelligence. With a blending of advanced analytics and specialist ESG advisory, organisations are able to connect their sustainability ambitions with global best practice and build resilience for the long term.

Conclusion

The AI era is a turning point in business thinking around sustainability. With regulations like ISSB and CSRD mandating ESG disclosure, companies need answers that can keep pace with growing data intricacy and stakeholder expectations. AI-driven ESG reporting offers the pace, precision, and transparency necessary to meet such expectations, allowing organisations to use compliance as a differentiator.

From facilitating data automation to checking emissions, risk prediction, and reporting compliance, AI brings ESG from a cumbersome activity to a smooth, strategic function. And, coupled with the right expertise, it assists organisations in spearheading alterations in frameworks and regulatory reforms.

Discover how Ikano Insight’s ESG Performance Optimiser (powered by Unravel Carbon) can make ISSB disclosure transparent, amplify data confidence, and propel your sustainability journey today.

Written by Innes Christison – (follow Innes on LinkedIn here)

Senior Sustainability Business Analyst

With experience as a Head of Sustainability and supply chain expert, Innes has helped brands including Tesco, KFC and Wowcher turn sustainability strategies into enablers for growth.

Expert in carbon passporting, measuring and managing carbon across the full supply chain, Innes now works with businesses across all sectors to simplify, streamline and optimise their entire ESG reporting requirements.