Twentieth International Conference on Technology, Knowledge, and Society

Abstract

Artificial Intelligence (AI) is a reality for most businesses while generative AI applications are at the top of the corporate agenda. Concurrently, there is a clear need for improving the sustainability performance of business processes. We are experiencing a climate crisis, and the culprit is likely carbon emissions. Consequently, governments have tightened environmental regulations. Moreover, customers, investors and stakeholders have shifted their mindset and Environmental, Social and Governance (ESG) indicators are now part of the decision of doing business with a company or not. To increase the complexity of the situation, AI has the reputation of being power hungry requiring increasingly large amounts of energy to run. It is arguable AI may be worsening the climate crisis. As a sign of hope, there are multiple industry cases of the application of AI as enablers of sustainable business practices. Evidently, there is a dichotomy at play. AI must be more sustainable. Alternatively, AI must be used as an enabler of sustainability. In this study we propose AI must do both. Businesses must employ AI for improving their ESG performance and at the same time, AI technologies must be deployed in environmentally sustainable ways. Hence, AI must produce a net ESG performance gain. The main challenges for a net gain approach are metrics and scenario analysis. The objective of this research is to conduct a survey of technology solutions accurately measuring ESG performance of businesses and analyze it to shed light on the hypothesis of AI producing a net ESG impact.