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 Kumar, P. Arun; Aranha, Rekha; Thaliyan, Delma Title A name given to the resource AI for Fair Recruitment: Balancing Tech and Ethics 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 Impact of Artificial Intelligence on Data-Driven Decision Making in HR for Revolutionizing Organizational Growth;pp.253-270 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1108/978-1-83662-982-520251014" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/978-1-83662-982-520251014</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105023457053?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023457053?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 Kumar P.A., Christ University, Bangalore, India; Aranha R., Christ University, Bangalore, India; Thaliyan D., Christ University, Bangalore, India Description An account of the resource Purpose: This chapter's objective is to examine how artificial intelligence (AI) is influencing the development of human resource management (HRM) systems, focusing on recruiting, developing employees, and increasing the diversity of the workforce by reducing bias. Design-methodology-approach: The investigation adopted a two-phase research strategy. First, bibliometric analysis of AI-HRM evidence received attention from most scholars indicating major topics of concern within the AI and HRM corpus. Second, a systematic literature review (SLR) based on these themes and applied focus key strings and PRISMA protocols to ensure satisfactory efforts in locating and discussing the relevant literature. Findings: The bibliometric analysis suggested three points of interest that are popular in the literature: AI in recruitment and diversity, employee development, and bias reduction. These programs can be used from mere training employees to including operational supervision and engagement. The case studies featured some well-known brands such as Unilever, Accenture, and IBM. The results indicate a possibility that AI will assist in the advancement of HRM processes, foster diversity, and inclusiveness and even bias-free recruitment and development of employees. Practical implications: The chapter proposes guidelines for the ethical application of AI in HR, including meticulous data collection, algorithmic design, and routine supervision. It emphasizes that AI possesses transformative potential for achieving diversity and inclusion in workplaces. Originality: This chapter expands on the ongoing discussion of AI in HRM by providing a bibliometric approach and SLR, making a new and substantiated claim on Al's role in promoting diversity and reducing biases. 2025 by Arun Kumar P, Rekha Aranha and Delma Thaliyan. All rights reserved. Subject The topic of the resource Artificial intelligence; Bias; Diversity; Human oversight; Recruitment Publisher An entity responsible for making the resource available Emerald Publishing Relation A related resource ISBN: 978-183662982-5; 978-183662983-2; 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