Practical AI Cases for Solving ESG Challenges

Abstract

Artificial intelligence (AI) is a rapidly advancing area of research that encompasses numerical methods to solve various prediction, optimization, and classification/clustering problems. Recently, AI tools were proposed to address the environmental, social, and governance (ESG) challenges associated with sustainable business development. While many publications discuss the potential of AI, few focus on practical cases in the three ESG domains altogether, and even fewer highlight the challenges that AI may pose in terms of ESG. The current paper fills this gap by reviewing practical AI applications with a main focus on IT and engineering implementations. The considered cases are based on almost one hundred publicly available research manuscripts and reports obtained via online search engines. This review involves the study of typical business and production problems associated with each ESG domain, gives background details on several selected cases (such as carbon neutrality, land management, and ESG scoring), and lists challenges that the smart algorithms can pose (such as fake news generation and increased electricity consumption). Overall, it is concluded that, while many practical cases already exist, AI in ESG is still very far away from reaching its full potential; however, one should always remember that AI itself can lead to some ESG risks.

Strategic Integration of Artificial Intelligence for Sustainable Businesses: Implications for Data Management and Human User Engagement in the Digital Era

“…By leveraging AI and Big Data for predictive analytics, for-profit companies cannot only meet but also anticipate their clients' expectations. Such a proactive approach has been analyzed by Rutter [43] and Burnaev [44], and the results of the study showed improved client interactions. One of the primary benefits of AI and Big Data integration in interactions with clients is the ability to offer highly personalized products and services to clients, which has been very much studied by various researchers from the aspect of business effectiveness and business efficiency or precision [45,46].…”