{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T14:17:55Z","timestamp":1790000275752,"version":"4.0.1"},"reference-count":59,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T00:00:00Z","timestamp":1789948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behav. Sci.","Behavioral Sciences"],"abstract":"<jats:p>This study investigates employee perceptions of artificial intelligence (AI) in the field of recruitment and selection in Saudi Arabian companies. While the use of recruitment systems based on AI is growing, their acceptance by organisations is influenced by whether employees consider these systems to be useful, transparent, and fair, and how this affects their professional judgement. This study is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Socio-Technical Theory (STT) and explores a two-path explanatory model. Perceived usefulness is linked to perceived AI effectiveness in the AI-related pathway and is associated with transparency of AI, trust in AI systems, and organisational support for AI use. On the HR pathway, there is a negative association between technostress and HR support and readiness, while clarity of integration of AI is positively associated with HR support and readiness. The sample comprised 450 purposively selected respondents from Jeddah, Riyadh and Dammam, and data were analysed using Structural Equation Modelling (SEM) in AMOS. The perceived effectiveness of AI and HR\u2019s support\/readiness for AI was positively and significantly correlated with employee perceptions of AI in recruitment and selection. The relationships of these data should be interpreted as structural relationships; since the data are cross-sectional, they cannot be interpreted as causation or mediation. Further methodological issues include common method bias since all constructs were assessed via self-report and in the same questionnaire.<\/jats:p>","DOI":"10.3390\/bs16091708","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:50:03Z","timestamp":1789995003000},"page":"1708","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Navigating the Human Side of AI: A Socio-Technical Model of Employee Attitudes Toward Algorithmic Recruitment"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0943-0317","authenticated-orcid":false,"given":"Hasan","family":"Beyari","sequence":"first","affiliation":[{"name":"Department of Administrative and Financial Sciences, Applied College, Umm Al-Qura University, Makkah 24382, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e64266","DOI":"10.2196\/64266","article-title":"Perceived trust and professional identity threat in AI-based clinical decision support systems","volume":"9","author":"Ackerhans","year":"2025","journal-title":"JMIR Formative Research"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1568","DOI":"10.1057\/s41599-024-04044-8","article-title":"Trust in AI: Progress, challenges, and future directions","volume":"11","author":"Afroogh","year":"2024","journal-title":"Humanities & Social Sciences Communications"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1186\/s13731-023-00324-w","article-title":"Implementing AIRM: A new AI recruiting model for the Saudi Arabia labour market","volume":"12","author":"Aleisa","year":"2023","journal-title":"Journal of Innovation and Entrepreneurship"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Almeida, F., Silva, A. 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