Publicação
Artificial intelligence in recruitment: a multivocal review of benefits, challenges, and strategies
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | |
| datacite.subject.sdg | 04:Educação de Qualidade | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.author | Trovão, Hugo | |
| dc.contributor.author | São Mamede, Henrique | |
| dc.contributor.author | Trigo, Paulo | |
| dc.contributor.author | Santos, Vitor | |
| dc.date.accessioned | 2026-01-06T15:34:52Z | |
| dc.date.available | 2026-01-06T15:34:52Z | |
| dc.date.issued | 2025-12-01 | |
| dc.description.abstract | This study investigates the role of artificial intelligence (AI) in recruitment, with a specific emphasis on small and medium enterprises (SMEs) and cultural diversity, two dimensions frequently underrepresented in existing research. The objective is to evaluate the benefits, challenges, and strategies for the responsible adoption of AI in recruitment. To achieve this, a Multivocal Literature Review (MLR) was conducted, systematically synthesising peer-reviewed studies and grey literature published from 2018 onwards. Following Kitchenham’s systematic review guidelines and Garousi’s multivocal extensions, academic and practitioner perspectives were analysed to capture both theoretical insights and real-world practices. The findings indicate that AI can streamline recruitment processes, improve decision-making accuracy, and enhance candidate experience through tools such as résumé screening, predictive analytics, and generative AI applications. However, issues of algorithmic bias, limited transparency, data quality, regulatory compliance, and workforce scepticism persist, particularly in SMEs that face resource constraints. Although much of the available evidence reflects Western contexts, this review broadens the scope by integrating global perspectives and highlighting how cultural and regional factors influence AI acceptance. The novelty of this study lies in combining academic and industry evidence to propose actionable strategies—such as bias audits, explainable AI frameworks, and human-in-the-loop approaches—for more inclusive, sustainable, and globally relevant adoption of AI in recruitment. | por |
| dc.identifier.doi | 10.28991/ESJ-2025-09-06-030 | |
| dc.identifier.issn | 2610-9182 | |
| dc.identifier.uri | http://hdl.handle.net/10400.2/20657 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Ital Publication | |
| dc.relation | UID/50014/2025 | |
| dc.relation.hasversion | https://ijournalse.org/index.php/ESJ/article/view/3514 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Artificial intelligence | |
| dc.subject | Generative AI | |
| dc.subject | Large language models | |
| dc.subject | Human resource management | |
| dc.subject | Recruitment | |
| dc.subject | AI ethics | |
| dc.subject | SMEs | |
| dc.title | Artificial intelligence in recruitment: a multivocal review of benefits, challenges, and strategies | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 3485 | |
| oaire.citation.issue | 6 | |
| oaire.citation.startPage | 3458 | |
| oaire.citation.title | Emerging Science Journal | |
| oaire.citation.volume | 9 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Trovão | |
| person.familyName | São Mamede | |
| person.familyName | Trigo | |
| person.familyName | Santos | |
| person.givenName | Hugo | |
| person.givenName | Henrique | |
| person.givenName | Paulo | |
| person.givenName | Vitor | |
| person.identifier | R-002-0P0 | |
| person.identifier.ciencia-id | 7F17-9DAD-C007 | |
| person.identifier.ciencia-id | F011-8BE3-FEB1 | |
| person.identifier.orcid | 0000-0002-6206-745X | |
| person.identifier.orcid | 0000-0002-5383-9884 | |
| person.identifier.orcid | 0000-0001-5850-615X | |
| person.identifier.orcid | 0000-0002-4223-7079 | |
| person.identifier.scopus-author-id | 36458782500 | |
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