Overcoming ESG Measurement and Reporting Nuisances with AI

Tensions are once again rising around environmental, social, and governance (ESG) reporting

On the one hand, there is growing concern among corporate leaders and boards that ESG is costly, ineffective, and politicized. On the other hand, the U.S. Securities and Exchange Commission (SEC) is working harder than ever to crack down on misleading claims with a cluster of new restrictions set to verify that ESG funds correctly specify their investments. All the while, investors and activists are calling for more transparency into the real impact on business, communities, and the environment.   

One part of the problem is that ESG frameworks are inconsistent. There are a wide variety of ESG frameworks within each industry, making it difficult to set standards and compare progress. Another factor is that ESG efforts can be extremely difficult to accurately measure, indicating that even when organizations are reporting promising ESG efforts, there’s a possibility those efforts might still be below par.   

Fortunately, several best practices for setting and achieving ESG goals have emerged over the past few decades alongside new technologies for monitoring and reporting. Internet of Things (IoT) and artificial intelligence (AI) technologies offer an opportunity to greatly improve ESG measurement and reporting, which will ultimately lead to better outcomes for all stakeholders.  

AI’s Role in Optimal ESG Reporting  

Amidst the heightening focus on ESG efforts, organizations are searching for insights into how to set and achieve ESG goals without excessive costs or efforts. Today, companies can accomplish this by employing AI and other technologies to create achievable goals and report their progress to all parties involved.   

AI has entered the realm of ESG reporting due to the enormous growth of data in recent years. The opportunity for harnessing data from IoT devices, like sensors, and using it to an advantage is only increasing. When it comes to ESG efforts, companies can combine AI and data to understand a variety of things, like whether the materials it’s buying meet sustainability standards. The power of AI lies in its ability to take time-consuming data management out of human hands and boil that data down into something highly relevant and useful.  

There are best practices to consider when it comes to ESG goal setting and measurement that can help companies stay on top of this important task. Thanks to the addition of AI, these once-tedious chores will quickly become parts of a painless, fully automated process.  

Keep a document trail: To prove that the company has a clear history of complying with both its own and any legal ESG requirements, maintaining a document trail can serve as proof of its efforts to stay within the defined standards. This is also where AI can be helpful, as keeping track of and sorting through these documents can be laborious. AI with metadata capabilities can automate this task so that the needed documents are available at a moment’s notice, making it easier to report progress.   

Generate SMART metrics: Developing Specific, Measurable, Achievable, Relevant, and Time-bound metrics is key to achieving and recording ESG progress. AI can help companies understand whether the metrics that are being set are SMART. Hybrid AI technology, which combines data-driven automation with human-like reasoning, can provide accurate predictions to guide metric setting by reviewing both data and historical knowledge to determine realistic goals.   

Maintain a unified data management platform: Companies are drowning in data. For example, a typical refinery has hundreds of thousands of sensors that are generating data every second. Artificially intelligent data management platforms can filter through this data in real time and only alert humans when it is important — like when energy and other precious resources are being wasted. With this visibility, companies can stay on track with their goals by having an accurate picture of where they can save energy and reduce carbon emissions.  

Use an ESG advisor: Hiring an ESG advisor can help organizations leverage key learnings from others but tends to be costly. These days, AI software serves as a cheaper, effective alternative to human advisors. The software can advise companies on which ESG practices have proven to be reliable and effective and which practices should be avoided.  

Better ESG Measurement 

When it comes to ESG measurement, AI technologies can augment once-tedious practices to save both time and money while complying with the SEC and the wants of stakeholders. As artificial intelligence technologies become more advanced, organizations are continuing to harness their potential to improve data quality and analytics. This is particularly useful for ESG measurement and reporting, where data methodologies are sorely lacking. Employing AI alongside other best practices for ESG goal setting, measurement, and reporting can help organizations meet their goals while preserving the bottom line.  

About the Author

Richard Martin, Senior Vice President at AI software company Beyond Limits, is a proven business executive with over thirty years of experience growing software companies through value creation within the process industry. Richard’s broad experience in sales, business development, marketing, company and solution strategy, partner programs, and operations stem from his roles at top companies like Texas Instruments, AspenTech, and Aveva. Richard has a bachelors of science in chemical engineering from the University of Mississippi.   

 Featured image: ©Juanjo