Why AI is the future of the ESG roadmap
By Laure de Saint Germain, Global Director, Finance Solutions at Board International
The business landscape is evolving and so too are consumer expectations. In the past, price was often the sole deciding factor when it came to purchasing decisions, but now many other considerations are also at play. Chief among these is a company’s environmental, social and governance (ESG) stance, with green credentials now firmly in the spotlight amongst environmentally minded customers and investors.
This shift in behaviour has given rise to the unsavoury practice of ‘greenwashing’ amongst more unscrupulous businesses. Greenwashing involves the use of misleading marketing campaigns and PR activity to give the impression that sustainable business practices are in place when, in reality, that often isn’t the case. Perhaps unsurprisingly, greenwashing is much more rampant in some sectors than others, with food, drink and fashion industries being some of the worst offenders. However, customers are waking up to greenwashing in ever-growing numbers and they’re no longer willing to tolerate it. Instead, they’re demanding full transparency and are increasingly willing to vote with their wallets, only buying from brands that can prove their supply chain, ethical practices, and approach to compliance are as good as they claim to be.
The first step for retailers on the path to true sustainability is to operationalise decisions around buying. Instead of focusing purely on profit margins, retailers need to make the buying process more three dimensional and consider which options have the smallest carbon footprint. However, this is far from easy, given the length of many global supply chains today. Even when a company has the best intentions, it can be very difficult to determine if suppliers and partners are being entirely truthful about their own sustainability practices or if they are engaged in greenwashing themselves.
AI technology is redressing the balance
ESG data can be extremely complex, combining both qualitative and quantitative datasets from across the business and entire supply chain. Consequently, manually collating and analysing such huge amounts of information is very difficult to do.
For this reason, artificial intelligence has quickly come to the fore as a key technology when it comes to ensuring ESG compliance. This is because that enables businesses to aggregate, process, interpret, and summarise pertinent information in a fraction of the time it would take a dedicated group of analysts to do the same.
When managed correctly, the technology is ideally suited to automating a wide range of ESG related data tasks. Furthermore, its ability to combine this data with other sources without needing to separate it out into different environments is key to effective ESG planning, which requires businesses to be able to track, monitor, and adjust according to varying sustainability goals.
The optimal way to use AI in this scenario is to collect, standardise, and aggregate data for each metric involved in ESG reporting. Once these are in place, businesses can gain a much better understanding of their individual targets, enabling them to create an ESG framework that will hold.
For those wanting to take it further, combining machine learning, generative AI, and video/image processing can provide businesses with an even broader and more comprehensive understanding of their data. Integrating natural language processing also allows analysts to interrogate the data and generate plain-English analysis, automate ESG report creation processes, and potentially reduce errors as a result.
Not a silver bullet
The power of AI to do good is undeniable, but as a technology still in its relative infancy, it’s important to note that it’s not without its issues either. AI experts warn that issues with incomplete or biased source data means the accuracy rate of current AI tools can fluctuate significantly. Consequently, any company using it for ESG purposes should either verify output from public-facing tools or opt for proprietary tools that only use data from smaller, verifiable data sets.
According to ESG strategy expert John Friedman, companies should also document how ESG solutions with AI will be evaluated as a critical part of the governance framework. This includes ensuring the technology is fit for purpose, understanding how the system is built to make sure it is robust enough, and analysing the providers’ past track record for building solutions that comply with regulatory requirements.
While greenwashing is a communication exercise, its intent is to restore a brand or an image. It is far from true business management and governance. Greenwashing had its time, but now companies are working towards building long term sustainability as it’s becoming increasingly crucial to get it right. And with that comes the complexity of seeing it through. For those looking to achieve truly sustainable operations, AI technology offers a powerful way to not only ensure their own ESG targets are being hit, but to weed out and sever ties with partners and suppliers that don’t share their goals.
Uma Rajagopal has been managing the posting of content for multiple platforms since 2021, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune. Her role ensures that content is published accurately and efficiently across these diverse publications.