AI and ESG: Is there a clear solution?

ESG is vastly becoming more important for global businesses, as they work to assess an organisation's business practices and performance on various sustainability and ethical issues.

During the recent UK AI Safety Summit at Bletchley Park, world leaders and industry experts reflected how this subject is becoming more of a priority in connection with AI, as larger enterprises are already concerned about implications such as job losses as a result of AI.

Concerns around ESG investing, and ESG more broadly, are continuing to grow across industry leaders and regulators globally, ultimately leading to more companies seeking to redefine their strategies in efforts to stay ahead.

Businesses working together to improve ESG transparency and performance

According to C3.ai, companies across essential industries today are using enterprise AI to address the most pressing ESG challenges. These include translating commitments into plans, establishing unified data visibility for reporting and decision-making and proactively engaging key stakeholders to manage risks and capture valuable opportunities.

AI already holds huge potential to revolutionise key industries and so major ESG players have been experimenting and collaborating with each other to enhance ESG ratings outputs. These types of AI and machine learning tools can be used for the optimisation of services, including data management and reporting, in addition to enabling workers to make more informed and efficient business decisions.

A crucial example is via environmental management, highlighting how AI could be useful in mitigating some of the effects of climate change, as well as facilitating necessary business adaptation. In particular, researchers on Google’s Climate & Energy team have partnered with American Airlines and Breakthrough Energy to work towards developing AI contrail forecast maps to test if pilots can choose routes that avoid creating contrails.

This type of technology could be instrumental in how enterprises and world leaders consider how digital tools can be used with a sustainable objective.

However, there is already the risk of social dangers associated with AI, as it could be used by ‘bad actors’ irresponsibly. There are already reports of bias and unethical systems associated with AI, highlighting how essential it is for businesses to consider responsible use cases of AI, machine learning and GPT models.

In the midst of greater regulations being enforced and companies racing to achieve more sustainable practices, the development and deployment of new AI and machine learning systems in relation to ESG strategies must be ethical in order to benefit businesses.

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