The Influence of Artificial Intelligence Adoption in HRM on Recruitment and Selection Efficiency

M. Yusuf; Mulyadi; Muhammad Ferdiananda Chadafi; Muchsin

doi:10.37641/jimkes.v14i1.4600

Authors

M. Yusuf Universitas Islam Kebangsaan Indonesia, Indonesia
Mulyadi Universitas Islam Kebangsaan Indonesia, Indonesia
Muhammad Ferdiananda Chadafi Universitas Islam Kebangsaan Indonesia, Indonesia
Muchsin Universitas Jabal Ghafur, Indonesia

DOI:

https://doi.org/10.37641/jimkes.v14i1.4600

Keywords:

AI Adoption, Digital Maturity, HR Analytics Capability, Recruitment Efficiency, Selection Efficiency

Abstract

This study examines the impact of artificial intelligence adoption in human resource management on recruitment efficiency and selection efficiency in Indonesia. Drawing on the resource-based view framework and the human resource analytics literature, we propose that artificial intelligence enhances efficiency through human resource analytics capability (as a mediator), while organizational digital maturity, firm size, and job complexity moderate the strength of these effects. Data were collected from n = 200 recruitment/selection units across sectors; a multi-source approach combined survey measures (AI adoption, HR analytics capability, digital maturity, job complexity) and operational HR metrics (time-to-fill, cost-per-hire, selection ratio, assessment throughput, offer acceptance, and early attrition ≤ 6 months). SEM analysis shows that artificial intelligence adoption has a significant positive effect on recruitment efficiency and selection efficiency. Human resource analytics capability partially mediates the effect of artificial intelligence on both outcomes. Moderation results indicate that the effects of artificial intelligence are stronger in organizations with high digital maturity and larger size, but weaken for positions with high job complexity. These findings imply that organizations should align artificial intelligence investments with the development of HR analytics capability and digital readiness to maximize efficiency gains in recruitment and selection.

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