Using AI to add value to ESG reporting

With the ability to strategically apply AI in ESG reporting, understanding AI’s parameters and where it can be most effective in reporting on ESG factors is a crucial first step. This understanding helps reduce the hidden risks that can negatively impact reporting. So, in what situations can AI help add value to ESG reporting, and how?

Rationalising governance decisions

The ability to apply logical analysis is a clear benefit of AI as it removes the emotional influence that can often interfere with good governance. Taking bribery as an example, AI’s analytical and strictly database-driven capacity adds a more rational approach to decisions that could be more easily compromised by human emotion. The big benefit of AI in governance is that it can analyse vast amounts of data more thoroughly and accurately than humans alone, helping to avoid bribery or conflict of interest situations.

Predicting social factors

AI’s predictive capabilities are a significant asset in reporting on social factors. By analysing data sets from departments such as human resources, companies can predict strengths and weaknesses in their approach to equality targets related to, for example, gender diversity. This predictive ability provides a digital overlay to improve the selection process of candidates more strategically, by streamlining and automating various aspects of recruitment. Of course, as with all aspects of reporting on social factors, it is essential that AI systems are developed and trained so that fairness is embedded at the outset and potential biases are monitored.

Monitoring less visible environmental factors

From recycling materials to moving to green energy, the ability to report on a company’s carbon footprint is gaining traction. While AI can help analyse these more measurable environmental impacts, there are less visible environmental factors coming to the fore that companies should now begin to consider. As companies migrate to a more digitalised business platform, the increase in energy used will potentially have a more significant negative impact on the environment than, for example, deforestation or plastic waste. While the quantifiable nature of energy consumption allows corporations to use technology such as AI to calibrate their digitalisation deployment, it is crucial to maintain an equilibrium to prevent the potential benefits from being overshadowed by the adverse effects of excessive energy use.

Furthermore, companies should not only carefully monitor the impact of digitalisation on business operations, including the use of AI itself, but also factor in the overall efficiency of the technology used. This includes the use of software and hardware, as well as the location of data centres and the types of energy sources feeding them.

By carefully assessing ESG reporting factors, companies can improve their understanding of how to optimise AI and in what situations it can add the most value. This includes some innovative applications on using AI for ESG reporting, such as analysing waste and drawing conclusions about the effectiveness of waste segregation, intelligent climate and lighting control in the office, and measuring environmental damage using satellite imagery.

Importantly, taking the time to consider how AI solutions accurately reflect your ESG needs and targets will help achieve the right balance between innovation and successful implementation.