Is ESG ready for AI?

By Saba Ahmad

In the midst of the AI frenzy, as industries rush to harness its potential, should we use AI to enhance the critical domain of ESG?

ESG frameworks have been heralded as a measurable way to hold corporations accountable, converting ideas into measurable KPI’s. Amidst this backdrop, the integration of artificial intelligence (AI) is heralded as a transformative force that can enhance ESG frameworks improving: data analysis in carbon footprint tracking, supply chain transparency, ESG standards reporting, social impact assessment, and investment and risk analysis. However, like any tool the use of AI raises both opportunities and ethical concerns.?

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On the plus side, AI helps with efficiency, speed and accuracy in data collection.??

Gathering ESG data in almost real-time enhances accuracy, a key asset in ESG reporting and assessments. AI also allows us to analyse a larger array and combination of factors in a much faster time. Faster generation of trend prediction based on historical data allows organizations to anticipate ESG risks and make decisions more quickly.?

One of the strongest benefits of AI for ESG lies in its ability to create new data sources which can be added to predictive analytics – enhanced prediction leading to enhanced decision making. Natural Language Processing (NLP) algorithms can scan and interpret a wide range of textual sources, such as news articles and social media, to gauge ESG related events and public sentiment and controversies in real-time.??

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On the flip side, the challenges of using AI in ESG are the same challenges everyone else has pointed to.?

Bias and lack of fairness in historical data can lead to unfair outcomes especially when examining the ‘S’ (Social) components.? Further, data privacy issues are not yet addressed and of course the issue of how resource intensive AI is especially as initial ML models are initially created and trained.??

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There are, however, two larger issues to worry about within ESG & AI – transparency and interpretability.??

ESG is a relatively new industry with new data points and data categorisation. The key concern here is that to procure data accuracy you need historical trends which are understood over time and hence trusted. This history and trust are still being gathered within ESG. When lacking sufficient historical data there can still be analysis, however, it needs to be fully transparent in order to understand how algorithms are working so sound interpretations, and hence, decisions can be made by key stakeholders. The current lack of understanding of these ‘black box’ algorithms is extremely concerning as the ESG industry rushes to validate itself; ironically an industry which is in fact set up and meant to catch out these discrepancies in the first place.??

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The potential for AI to enhance data analysis and decision-making in the ESG sector is vast. It can drive efficiency, accuracy, and provide valuable insights that aid in meeting sustainability goals. However, the ethical challenges cannot be overlooked. Addressing bias, ensuring transparency, and safeguarding data privacy are prerequisites for responsible AI implementation.?

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ESG and sustainability stakeholders must approach AI integration with cautious optimism. While it holds the promise of transformative change, it requires careful planning, governance, and ongoing evaluation to maximize its benefits while minimizing risks. Ultimately, AI can be a powerful tool, but it must be wielded wisely to advance the global agenda of sustainability and responsible corporate behaviour.?

About the Author

Saba has over 20 years of experience developing data driven marketing solutions for large Fortune 500 brands across US, Asia and UK, in various industries including finance, retail, restaurant & NGO's. She manages teams of data scientists, developers, analysts & project managers to deliver the best outcomes for clients. Sabahas a M.A. in Sociology, Consumer Behavior from DePaul University and a B.A. in Economics and Sociology from Knox College in Chicago. She has published articles in magazines on various topics including diversity bias in advertising, is the co-host of a social entrepreneur podcast called The ProSocialSocial and a philanthropist, advocating for refugees, education and sports. She sits on various boards and is co-founder to two early stage startups.

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