Beyond Efficiency: Understanding Job Candidates' Acceptance of AI-enabled Recruitment: A Socio-Technical Perspective

Artificial Intelligence (AI) is increasingly reshaping recruitment processes by automating candidate screening, interviews, and hiring decisions. Despite its growing adoption, AI-enabled recruitment tools raise significant ethical and psychological concerns among job candidates, particularly regarding fairness, transparency, risk, and trust. Addressing a notable research gap concerning candidate perspectives, this study aims to investigate job candidates’ acceptance of AI-enabled recruitment tools, examining how perceived usefulness, ease of use, fairness, transparency, and risk influence their attitudes, mediated by trust and moderated by AI experience. Drawing on the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Fairness, Accountability, Transparency, and Explainability (FATE) framework, the study introduces a socio-technical conceptual model to address the identified research gap. A quantitative survey was conducted with 143 job applicants in Jordan’s pharmaceutical sector. The data were analysed using SPSS multiple regression analysis to assess the relationships among the variables. The findings show that perceived fairness, transparency, usefulness, and trust significantly shape positive attitudes toward AI-enabled hiring. Whereas ease of use and risk perceptions are less influential, trust proved to be a vital mediator, particularly between job applicants' perceptions of fairness and transparency and their attitudes toward AI-enabled recruitment tools, while prior AI experience moderates the influence of transparency and risk perceptions. The study concludes that respondents placed greater importance on AI's ethical and relational characteristics than technical functionality, highlighting the importance of designing functionally efficient, but also ethically responsible, fair, trustworthy, and transparent AI-enabled recruitment tools to promote candidates’ acceptance and enhance responsible AI adoption in emerging labour markets.