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Artificial intelligence applied to potential assessment and talent identification in an organisational context

2023Journal article Restricted access
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dc.contributor.authorFrança, Tiago Jacob Fernandes
dc.contributor.authorSão Mamede, Henrique
dc.contributor.authorBarroso, João Manuel Pereira
dc.contributor.authorSantos, Vítor Manuel Pereira Duarte dos
dc.date.accessioned2023-06-06T10:02:46Z
dc.date.available2023-06-06T10:02:46Z
dc.date.issued2023
dc.description.abstractOur study provides valuable insights into the relationship between artificial intelligence (AI) and Human Resource Management (HRM). Using a systematic literature review and the PRISMA statement, we have minimised bias and ensured reliable findings. Our comprehensive synthesis of the included studies, along with a bibliometric analysis of articles, journals, indexes, authors' affiliations, citations, keyword co-occurrences, and co-authorship analysis, has produced robust results. The discussion of our findings focuses on key areas of interest, such as AI and Talent, AI Bias, Ethics and Law, and their impact on Human Resource (HR) management. Our research highlights the recognition by organisations of the importance of talent management in achieving a competitive advantage as higher-level skills become increasingly necessary. Although some HR managers have adopted AI technology for talent acquisition, our study reveals that there is still room for improvement. Our study is in line with previous research that acknowledges the potential for AI to revolutionise HR management and the future of work. Our findings emphasise the need for HR managers to be proactive in embracing technology and bridging the technological, human, societal, and governmental gaps. Our study contributes to the growing body of knowledge on AI and HR management, providing essential insights and recommendations for future research. The importance of our study lies in its focus on the role of HR in promoting the benefits of AI-based applications, thereby creating a larger body of knowledge from an organisational perspective.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.heliyon.2023.e14694pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.2/13983
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectHuman resourcespt_PT
dc.subjectPotential assessmentpt_PT
dc.subjectTalent managementpt_PT
dc.subjectNext-gen HRpt_PT
dc.titleArtificial intelligence applied to potential assessment and talent identification in an organisational contextpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue4pt_PT
oaire.citation.startPagee14694pt_PT
oaire.citation.titleHeliyonpt_PT
oaire.citation.volume9pt_PT
person.familyNameSão Mamede
person.givenNameHenrique
person.identifierR-002-0P0
person.identifier.ciencia-id7F17-9DAD-C007
person.identifier.orcid0000-0002-5383-9884
person.identifier.scopus-author-id36458782500
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication86fd6131-eed5-42be-9639-9466ddf680ab
relation.isAuthorOfPublication.latestForDiscovery86fd6131-eed5-42be-9639-9466ddf680ab

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