Harnessing Technologies and Data to Accelerate and Operationalize Environmental, Social, and Governance (ESG) Initiatives

Arif Perdana () and Seck Tan ()
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Arif Perdana: Monash University
Seck Tan: Singapore Institute of Technology

Chapter Chapter 12 in Digital Transformation in Accounting and Auditing, 2024, pp 347-375 from Springer

Abstract: Abstract Technology and data play a critical role in accelerating environmental, social, and governance (ESG) efforts. By leveraging ESG data and tools, organizations can identify, monitor, and mitigate ESG threats and business impacts. With the advent of data-driven technologies such as the Internet of Things, artificial intelligence (AI), and sensors, companies can easily collect and analyze large amounts of data about their supply chains and operations. In addition, blockchain technology can help companies improve transparency and authentication of ESG impacts. ESG goals could thus be identified, targets set, and improvements assessed. AI algorithms can identify correlations and trends between ESG performance metrics such as energy consumption, resource use, pollution, and stakeholder engagement. Companies can also supplement their AI capabilities with alternative data sources. Nevertheless, AI can pose a potential threat to companies and jeopardize ESG if not properly regulated. Implementing competent data governance protocols is critical to ESG efforts. Tracking and documenting ESG progress and avoiding potential complications in advancing AI requires accurate and reliable information. In this paper, we provide a conceptual analysis of the role of these technologies in advancing ESG initiatives. We outline strategies for companies to effectively leverage data as a valuable resource in support of these initiatives, increasing the benefits and mitigating the associated risks.

Keywords: Technology; Data; Environmental; Social; And Governance (ESG); Artificial Intelligence (AI); Blockchain technology; Data governance (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-46209-2_12

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DOI: 10.1007/978-3-031-46209-2_12

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