ESG Data Challenges: AI as a Solution

Today, organisations face an enormous compliance challenge in understanding and demonstrating their Environmental, Social and Governance (ESG) credentials

The foundations of ESG reporting are built on data, yet simply learning the ‘lay of the land’ is no longer enough – organisations must be able to identify and assemble enterprise data across their entire supply chain, in all operations and jurisdictions.

Compounding the issue are complex corporate structures. Legally relevant data is often siloed; whether that be across various cloud storage environments, different computers due to Bring Your Own Device and remote working, or even in the minds of employees following personnel changes.

The scale of this challenge is obvious, but with next-generation technology like AI at organisations’ disposal, difficulty is no longer an excuse.

Walking the Talk

With ESG set to remain a major compliance responsibility in the coming years, organisations must turn to AI technology as a solution. Not only can AI facilitate the smoother implementation of an organisation’s ESG policies, but it can also help to ensure they uphold their commitments and policies in dealings with customers and suppliers. Importantly, AI will also help organisations to maintain their ESG program as operations scale and data proliferates in the wake of increased headcount and expanded operations across different territories.

Take climate risk, for instance. Advanced technology can comprehensively track critical indicators such as raw material sourcing, carbon emissions and electronic waste. The latest advances in AI mean that you can track exposure across your existing contracts and, for the first time, all incoming contracts too. Given that accusations of greenwashing lie in wait for those who fake or exaggerate their eco-credentials, organisations cannot afford to get this wrong.

Three Major Benefits of AI for Meeting ESG Targets

So, what does this mean in practice? Let’s imagine a global energy company based in the UK needs to review and understand its contractual landscape, so it can assess its ESG position and exposure to any changes in legislation. Historically, manual contract review was the only way to do this, causing a significant drain on resource. But using AI, this company could gain three major benefits and improve its overall ESG approach.

Firstly, AI would provide an instant understanding of the company’s existing ESG position. For instance, AI could instantly flag all anti-bribery clauses present in the contracts – as well as highlighting those where such provisions are not included. Furthermore, AI could highlight out-of-the-box all governing laws across contracts, allowing the company to easily gauge its operations and exposure to any volatile regions or countries that have not, for example, signed up to the pledges made at COP26.

Secondly, AI would help organisations understand their documents in a more intelligent way. At present, many companies rely on manual searching or more basic technologies to find answers within their documents. Yet the former involves a vast amount of time and expense, whilst the latter can put organisations at risk of missing something. By contrast, AI can understand concepts within documents in much the same way that a human brain does, forming links between ideas and ensuring lawyers gain the most thorough understanding. So, if this company were searching for mentions of ‘coal’ within their documents, as part of assessing climate risk, AI could recognise that words such as ‘emissions’ or ‘mines’ would likely also be relevant to the search, and thus should be included.

Finally, AI would not only help the energy company gain these critical insights from its existing documents, but also anticipate future changes in standards or regulation by adapting as social mores or laws shift. Modern AI can learn simply by being shown an example of how a concept should look. For example, should financial levies be imposed on non-renewable energy sources, AI just needs to be shown one instance of how clauses mentioning ‘dirty’ energy should be phrased when negotiating deals with suppliers. Following exposure to this one example, it will then be able to instantly flag every other document containing this clause, as well as any instances of non-compliance in all incoming documents after that.

AI to keep up with the pace of change

ESG now touches all legal and regulatory aspects of an organisation. Be that as it may, agile AI can remove many barriers to a fast, flexible and comprehensive review process by providing a system that can read and form a conceptual understanding of documents and data.

Using AI to perform contract harmonisation exercises in this way makes these reviews – and overall compliance – easier in the future by adapting to a new ESG landscape that is changing all the time, positioning organisations to succeed.

About the Author

Luke Taylor is a Subject Matter Expert at Luminance, the world’s most advanced AI for legal process automation. In his four years with the company, he has worked extensively with law firms and businesses spanning a diverse range of industries including banking, consumer goods and aviation, across more than 60 countries. Most recently, Luke has spearheaded the launch of Luminance Corporate, the company’s latest product which revolutionises the entire contract lifecycle process, from contract drafting and negotiation to post-execution analysis.

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