How AI Helps in Sustainability Reporting

How AI is Transforming Sustainability Reporting

At the centre of sustainability reporting stands systematic collection of data. It is the most fundamental factor in ESG reports that guides decisions and drives impactful decisions. 

This is where Artificial Intelligence can aid annual reporting exercises. According to the ESG Global Study of 2024 by the Capital Group, a significant share of respondents indicated plans to explore generative AI for analysing sustainability issues. AI has been transforming sustainability reporting. It is quick and can process high volumes of data to generate pertinent insights. 

The Role of AI in ESG and Sustainability Data Management

AI has an overarching role to play when it comes to ESG reporting exercises and sustainability data management. 

Here are some key tasks that can be automated through AI:

• Gathering and organising data from several sources
• Comprehensive analyses of gaps and inefficiencies
• Near real-time or more frequent tracking of emissions, where data infrastructure allows
• Opportunities and risk analyses
• Flagging high-risk supply chain entities and realigning with ethical practices
• Supporting alignment and mapping of data to one or more ESG frameworks

How AI Improves Accuracy, Efficiency, and Compliance in Sustainability Reporting

AI in ESG reporting has been reshaping the world of ESG reporting and sustainability data management. Here’s how:

Gathering Data

AI tools can be built or configured to collect information from integrated data sources and then compiled systematically. Classification of data in alignment with guidelines is thus simplified, and businesses are able to save on time and cost.

Minimal Margin For Error

Sustainability reporting and AI can enhance factual accuracy in reports. They are designed to flag inconsistencies and can detect errors efficiently. Tools can also be configured to line up with select global sustainability guidelines like the GRI (Global Reporting Initiative) and CSRD (Corporate Sustainability Reporting Directive).

Timely Reporting

AI in sustainability reporting has been widely adopted due to its speed in providing effective resolutions to simple problems. It enables real-time tracking of emissions, pollution levels, and water usage in an enterprise, which can ensure timely reporting. This also helps forecast potential financial risks and opportunities early in the process.

AI Use Cases in Sustainability and ESG Reporting Workflows

Sustainability teams are increasingly adopting AI across a range of use cases:

• Data Collection and Validation

Financial materiality and impact materiality data can now be processed and checked for loopholes, anomalies, and errors. Decentralised data, like that from IoT sensors and satellites, can be compiled and validated through AI tools.

• Regulation Compliance

AI software and tools can be configured to operate in alignment with global ESG frameworks like the GRI, ISSB (International Sustainability Standards Board), CSRD, etc. Such exercises help single out business activities that are in compliance with existing ESG regulations and highlight potential gaps, inconsistencies, or areas of non-alignment that require human review.

• Communication & Engagement

Sustainability teams across the board use AI tools to make communication and stakeholder engagement easier. Translation of documents, communication via mail, and document summaries can be managed more efficiently and faster.

• Risk Management

Mapping risks is easier with AI. These technologies are built to understand numbers best and can process geographical and financial data to aid your business in the early detection of risks. AI tools can keep an eye out for news and updates to facilitate strategic planning and the prevention of loss.

Benefits of Using AI in Sustainability Reporting

By using AI, the sustainability teams of your business can work more efficiently and deliver reports without missing deadlines. Additional benefits include:

Enhanced Efficiency

Data extraction and analyses are quickened when using AI, in comparison to traditional manual reporting efforts. Data along the three ESG pillars of Environment, Social, and Governance is collected effectively while escalating inconsistencies or complications for intervention. 

Worry-free Compliance

AI tools can support compliance when used within clearly defined governance, controls, and human oversight. When configured through settings to comply with select ESG frameworks, sustainability reporting and AI can function to organise and generate regulation-compliant reports. While AI can reduce compliance risks, legal responsibility remains with the organisation.

Data-Powered Decision-Making

Real-time monitoring of data influences business decisions in a positive manner. When businesses are able to detect ESG risks early, they are able to prepare to be climate resilient. Sustainability reporting and AI working in tandem enhance business decision-making and enable organisations to track performance trends for preparing better reports.

Reduction in Costs

With a significant reduction in manual reporting effort, businesses are able to cut down on costs significantly. Additionally, early risk detection and efficient engagement with stakeholders prevent financial losses. 

Challenges and Limitations of AI in Sustainability Reporting

While AI in sustainability reporting can be incorporated to automate a large number of tasks, challenges persist for fully automating ESG analyses:

Dependency on Database

AI software cannot function independently to handle tasks from the data collection level to the report presentation. Data sources integrated with the software or AI stand at the centre of tasks that can be executed by the tool. In the absence of a database, the entire process comes to a halt.

Regulatory AI Permissions

Regulatory frameworks require human accountability and management responsibility, even when automation is used. Liability, in case of errors, continues to fall on human agents and the organisation. This limits the extent to which AI can be utilised for reporting on your business’s ESG status.

Technological Limits

AI in sustainability reporting can generate fictitious data when loopholes in information exist. Such technological limitations can hamper the credibility and quality of reports and lead to legal consequences as a result of non-compliance.

Future Outlook of AI in Sustainability and ESG Reporting

Including an element of human judgement along with tested AI models is going to become a fundamental reporting solution for businesses. As AI tackles real-time monitoring and risk prediction, human teams will act as a second layer of checks on the insights generated by software. Businesses will be able to free up valuable resources to focus on making strategic decisions and enforcing action plans for meeting ESG targets. 

Summary: AI In Sustainability Reporting

Classifying and analysing sustainability data across multiple aspects of the three ESG pillars can be automated through AI. It contributes to enhancing the efficiency of sustainability reporting and reduces additional costs and time spent on manual reporting.

Oren helps you create sustainability reports in a timely fashion. Through uncomplicated data collection and regulation-compliant analyses, your business is able to comprehensively report on ESG. Generate ESG reports with Oren that make an impact and adapt as per your business needs with our customisable solutions.

Frequently Asked Questions (FAQs)

1. How does AI help in sustainability reporting?

AI aids your business in automating a large number of sustainability reporting tasks like data collection, classification, and analysis. It helps your business create reports that align with global ESG frameworks and enhances efficiency in sustainability teams.

2. What role does AI play in ESG reporting?

AI in sustainability reporting helps organise data, benchmark disclosures, make real-time forecasts, identify risks and opportunities, and facilitate strategic decision-making.

3. Can AI improve accuracy in sustainability disclosures?

When integrated with credible databases, AI in ESG reporting is able to improve accuracy. It generates actionable insights and sustainability disclosures that are high-quality and credible.

4. How are sustainability reporting and AI used together for compliance?

AI software can be configured to align reports with regulational frameworks of your preferences and requirements, therefore, guaranteeing compliance in sustainability reporting.

5. What types of sustainability data can AI analyse?

AI in sustainability reporting can analyse data like GHG emissions, quantified waste management, pollution levels, geospatial data, social media engagement, etc.

6. Are there risks in using AI for sustainability reporting?

While an immensely efficient tool, there are certain limitations to using AI in sustainability reporting. Key risks include hallucinations and fictitious information, inability to function without databases, and limited capacity for verification.