A Panoramic Overview of the Opportunities and Challenges Artificial Intelligence Brings to ESG Investing

The twin transition involves two significant trends affecting future development models: sustainable transformation and digital transformation. The twin transition refers to not just two concurrent transformation processes, but also how to integrate them to accelerate necessary changes and bring society closer to the required degree of sustainable development. Understanding the relationship between artificial intelligence (AI) and the environment, society, and governance (ESG) is a critical challenge in the twin transition. This chapter presents a thorough analysis of the intricate interplay between AI technologies and ESG. First, the essay examines the ESG solutions offered by AI. The environmental perspective considers how AI may help tackle critical environmental concerns such as quantifying energy transition indicators, reducing greenhouse gas emissions, finding waste and pollution solutions, and launching internal climate change initiatives, among other things. The social viewpoint addresses how to optimize human resource deployment, candidate experience, and customized employee pension plans. The governance standpoint considers how AI might help improve governance and transparency by automating daily processes, detecting fraudulent activity, guaranteeing regulatory compliance, and identifying core materiality issues for a company. Second, the study examines the difficulties that AI presents for ESG practices. This includes large language models of electricity usage, carbon emissions, water management, and e-waste issues from an environmental perspective. The social angle sees it as a problem of labour substitution by AI, as well as potential algorithmic discrimination and amplification of the digital divide. From a governance standpoint, corporations’ use of AI encompasses data protection and security, transparency, ethical considerations, etc. Abuse and misuse of AI technology may potentially result in social dangers such as information cocoons and the spread of misleading information. Finally, the article suggests developing an AI governance framework using ESG methodologies. When firms employ AI, they must guarantee that the company’s application of AI is consistent with larger corporate principles. This paper will propose a six-dimensional framework for managing and developing AI in an ESG-compliant manner.