Policy Analysis: AI and Sustainability: Climate Impact Monitoring

Organizations are responsible for reporting two emission metrics: direct and indirect emissions. Reporting direct emissions is fairly standard given activity related to the generation of such emissions typically being performed within a controlled environment and on-site, thus making it easier to account for all of the activities that contribute to such emissions. However, indirect emissions stem from activities such as energy usage (relying on national grid estimates) and operations within a value chain that make quantifying such values difficult. Thus, the subjectivity involved with reporting indirect emissions and often relying on industry estimates to report such values, can unintentionally report erroneous estimates that misguide our perception and subsequent action in combating climate change. Leveraging an artificial intelligence (AI) platform within climate monitoring is critical towards evaluating the specific contributions of operations within enterprise resource planning (ERP) and supply chain operations, which can provide an accurate pulse on the total emissions while increasing transparency amongst all organizations with regards to reporting behavior, to help shape sustainable practices to combat climate change.