Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ramachandran, Ram B.; Gupta, Chabi Title A name given to the resource Can generative AI serve as the modern-day white-collar knowledge laborer? Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Financial Landscape Transformation: Technological Disruptions;pp.185-200 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1108/978-1-83753-750-120251010" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/978-1-83753-750-120251010</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000789214?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000789214?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramachandran R.B., O.P. Jindal Global University, Sonepat, Haryana, India; Gupta C., Christ University, Bengaluru, India Description An account of the resource Purpose: There has been a growing debate on whether generative AI can serve as the modern-day equivalent of white-collar knowledge workers. In a recent post, technology magnate Bill Gates boldly proclaimed that ChatGPT would soon become the quintessential white-collar worker of tomorrow (Dean, 2023). This is indeed an exciting prospect, as generative AI advances at breakneck speed. Need for the Study: This research delves upon the implications of such advancements for industries reliant on skilled employees. It raises questions about how these individuals will adjust their skillset going forward, given the proliferation of generative AI solutions poised to disrupt traditional roles previously occupied by humans. Methodology: The study uses an exploratory framework to understand AI's implications on job roles, productivity, and skill requirements. It introduces generative AI and its relevance, focusing on how it could transform whitecollar jobs. Findings: One thing seems clear: its impact on future employment opportunities. However, this technology still has limitations, potentially leading to unintended consequences. While capable of performing certain functions precisely and accurately, it cannot fully replace the reasoning abilities or cognitive flexibility innate in human workers tasked with knowledge-based work. Practical Implications: The potential implications for workforce development, policy-making, and future research in AI and labor economics are highlighted. This will also help gain insights into the integration process, benefits, challenges, and the changing nature of white-collar work due to generative AI. 2025 by Ram B. Ramachandran and Chabi Gupta. All rights reserved. Subject The topic of the resource Automation; Cybersecurity; Generative AI; Responsible AI; Technology; White-collar worker; Workforce development Publisher An entity responsible for making the resource available Emerald Publishing Relation A related resource ISBN: 978-183753750-1; 978-183753751-8; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online