@article{unic5575, month = {Diciembre}, author = {Archana Saxena and Rajesh Singh and Anita Gehlot and Shaik Vaseem Akram and Bhekisipho Twala and Aman Singh and Elisabeth Caro Montero and Neeraj Priyadarshi}, pages = {309}, volume = {15}, number = {1}, journal = {Sustainability}, year = {2022}, title = {Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape}, keywords = {ESG; sustainability; SDGs; Industry 4.0; IoT; artificial intelligence; big data; ESG reporting}, abstract = {Currently, sustainability is a vital aspect for every nation and organization to accomplish Sustainable Development Goals (SDGs) by 2030. Environmental, social, and governance (ESG) metrics are used to evaluate the sustainability level of an organization. According to the statistics, 53\% of respondents in the BlackRock survey are concerned about the availability of low ESG data, which is critical for determining the organization?s sustainability level. This obstacle can be overcome by implementing Industry 4.0 technologies, which enable real-time data, data authentication, prediction, transparency, authentication, and structured data. Based on the review of previous studies, it was determined that only a few studies discussed the implementation of Industry 4.0 technologies for ESG data and evaluation. The objective of the study is to discuss the significance of ESG data and report, which is used for the evaluation of the sustainability of an organization. In this regard, the assimilation of Industry 4.0 technologies (Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data for obtaining ESG data by an organization is detailed presented to study the progress of advancement of these technologies for ESG. On the basis of analysis, this study concludes that consumers are concerned about the ESG data, as most organizations develop inaccurate ESG data and suggest that these digital technologies have a crucial role in framing an accurate ESG report. After analysis a few vital conclusions are drawn such as ESG investment has benefited from AI capabilities, which previously relied on self-disclosed, annualized company information that was susceptible to inherent data issues and biases. Finally, the article discusses the vital recommendations that can be implemented for future work}, url = {http://repositorio.unic.co.ao/id/eprint/5575/} }