22 Sep How AI in ESG is supporting the drive net zero

Artificial intelligence is transforming the ESG industry, creating new opportunities and potential for businesses and investors through data analysis, reporting and clear, actionable insights. Differentiating between good and bad technology can be challenging. Industry experts continue to question the importance of human intervention in an industry that lacks standardisation and access to the necessary talent.

There has been a notable increase in the number of new disruptive platforms and services available in the ESG industry. As sustainability has become engrained in the corporate scene and targets become a critical element in legislation, ESG technology available to meet these changing requirements has become an industry in its form.

A study by PwC at the beginning of 2022 suggested that over 60% of corporate leaders believe ESG and sustainability to be critical in long-term business planning. Technology directly influences reaching these intentions, from reporting to climate risk assessments, governance plans and strategic road mapping. According to Brian Flynn, CTO at AI platform Rio ESG, the technology community is making a significant impact in this space, but not all platforms are created equal. Many are just pure technology concepts, failing to embrace innovation with industry expertise and insight. Flynn explains that many new apps are emerging from the tech community, offering services like carbon calculators, footprint assessments and other specialised products. The CTO of Rio ESG highlights that often these applications are lightweight, and there are questions about the completeness, data integrity and whether the products created involved contribution from experienced sustainability professionals. On the surface, these technology companies look good and provide a great user experience but quite often lack intelligence or transparency. 

Delivering on the ESG Experience

The democratisation of ESG involves leveraging the technology and in-house sustainability professionals to enable businesses of all sizes access to actionable insights that are typically unavailable. In the case of ESG Rio, they measure the current company position and use intelligent data analysis to acquire deeper insights on how to make improvements at a speed that suits each business.

Data is key to the process, and so onboarding clients requires detail to ensure the company gains the information to deliver the best quality. With the rise of ESG, businesses appreciate why companies like ESG Rio need this level of detail to produce the expected service.

One innovation since ESG that has emerged and expanded is the rise of data as a service (DaaS). This solution is delivered through exploring reports, public company details and natural language processes on documents, then extracting relevant information. It provides a method of understanding where businesses stand and a benchmark against industry standards. In the future, these services will play a vital role in automating ESG reports and infographics. Currently, most of the services available on the market stand more on the surface level, lacking the level of granularity needed.

Confidence with AI in ESG

Despite AI and ML, like ESG continuing on an accelerated path toward maturity, many industry experts still consider that much work is required to ensure customers gain the best value. For some time, AI and ML have created concerns around their impact on manual labour, but professionals like Flynn argue that AI should be viewed as an additional avenue to scaling up human skills rather than replacing them, especially in the case of ESG. In the ESG space, there is a lack of skilled talent with the required training and experience. Accelerating services like chatbot technology and target reports and digitising knowledge has been critical to expanding access to new, bespoke ESG services. Professional oversight and transparency are vital for delivering trust and quality in the service.

Like all new business platforms, we can only maximise the impact of this technology if the user is aware of its potential and functionalities. This process requires structured training processes and ensuring the user experience is as simple and streamlined as possible. The democratisation of technology is a critical process, but without proper training, very few people will be able to use a platform or service. The process needs to be as accessible as possible, which requires closer attention to automation. 

The assumption that acquiring big data, whether it be ESG or other, involves hiring more data scientists isn’t strictly the case. What is needed is for a business to incorporate its tech and services in ESG discussions. As tech solutions become more common, the tech leader shouldn’t necessarily be responsible for platform service selection and operations. Flynn explains that they typically discuss platform concepts with chief sustainability officers, CFOs and CEOs more than CTOs. A CTO will likely have insight into integrating platforms into other systems, but good governance requires making the technological input and knowledge available to everyone in a business.