ESG Series: AI’s influence in scaling ESG’s maturation

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AI’s evolution is stimulating fear as well as excitement

Scope of AI-driven ESG benefits

ESG risks resulting from the AI evolution

Transformational progress in artificial intelligence (AI) is stimulating fear as well as excitement. Large language models (LLMS) – the genus that powers ChatGPT, a generative AI tool – have surprised even their creators with its unprecedented reach given the sheer velocity this technology is being scaled.
Yet, a big problem is that they are black boxes and with the genie out of the bottle, today’s pulse advocates that it’s better to be safe (proceed pragmatically with AI’s transformative nature) than sorry (fall foul to its disruptive dynamics).

Unparalleled opportunities have been realised and we are yet to fully harness the power of AI to solve many of the world’s long-term sustainable challenges and promote ESG integration.
The circumvention of shortcomings with traditional ESG ratings; strengthening climate change modelling; promoting social responsibility by fostering inclusiveness and fairness; improving governance and transparency through compliance efficiencies; boosting the accuracy of corporate disclosures and; the ability to support ESG engagement, are all core beneficiaries of AI as an ESG value driver.

Yet, the rapid rise of AI throws into question ethical considerations which has the potential to create sustainability and environmental impediments that needs to be carefully calibrated.
AI models require a large amount of computational power that leads to high energy consumption (and associated emissions); governance challenges surrounding technological copyright violations; the risk of manipulation of corporate disclosures as communication methods adapt to algorithms and; considerations related to barriers to entry for new AI developers driving biases as well as a lack of consumer optionality, are equally core sustainability challenges of AI in the sphere of ESG’s evolution.

The common denominator in harnessing the power of AI to solve an array of ESG trade-offs remains engagement

What we are hearing from clients

Taken collectively, the bubbling mixture of transformation or disruption makes it complex to weigh AI’s distinctive opportunities and risks in fostering ESG’s burgeoning relevance. Lessons can be learned from other industries, and from past technological shifts. What is clear today is that AI produces answers that have the patina of truth, but often encompasses factual errors.
Regulation – moving at a snail’s pace relative to the platform shift in innovation – is needed to bring coherence to AI governance. If AI is as transformative a technology as vehicles and medicines then, like them, it will need new rules.
Overall, we hold conviction in the merits of the AI evolution to solve an array of ESG trade-offs, which on aggregate has the potential to transform the way we approach sustainability to foster a more equitable, and just society. Though, the transformative logic also pulls in the opposite direction – the cosmic speed at which the technology is moving is in itself the most disruptive from a social fabric dimension.
The common denominator in our view is engagement. Holistically, as AI’s usefulness becomes more pervasive, inclusive engagement amongst governments, regulators, corporates, investors and the finance sector will be imperative in pioneering forward AI’s influence in scaling ESG’s maturation.

AI will be more evolutionary than revolutionary but the evolution is acclerating.
Greater tendency for workforces to be reskilled rather than workforces to be decreased.
AI use commonalities are in product and service development as well as operations.
AI risk commonalities pertain to inaccuracies and intellectual property infringement.
Most AI-led cost decrease benefits are in the manufacturing sector whilst most AI-led revenue increases have been from marketing/sales.
AI technology bellwethers are trading at modest premiums, signalling that the AI-hype is not overdone.