The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes

Marian Nastase (), Gabriel Croitoru, Nicoleta Valentina Florea, Nicoleta Cristache and Ramona Lile
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Marian Nastase: Bucharest University of Economic Studies, Bucharest, Romania
Gabriel Croitoru: Valahia University of Targoviste, Targoviste, Romania
Nicoleta Valentina Florea: Valahia University of Targoviste, Targoviste, Romania
Nicoleta Cristache: Dunarea de Jos University of Galati, Galati, Romania
Ramona Lile: Aurel Vlaicu University of Arad, Arad, Romania

The AMFITEATRU ECONOMIC journal, 2024, vol. 26, issue 66, 421

Abstract: Managers increasingly want to improve the efficiency of human resources processes, and a solution with real results is Artificial Intelligence (AI), which provides real results in a virtual world for human resources managers, for companies, and also for candidates. The purpose of this article is to investigate the perception of employees in Romanian companies to adopt and use AI in recruitment and selection processes, analysing the factors that influence this acceptance intention using Technology Acceptance Model (TAM). The study aimed to determine the benefits of AI adoption in recruitment and selection processes, the perceived usefulness of adoption, and the ease of use in these processes. The results obtained showed that almost all the variables proposed for the model positively influenced the intention to accept and use AI in the recruitment and selection process. Non-discrimination and the utility of using (PU) AI in recruitment and selection had little influence. The findings should contribute to understanding the acceptance of artificial intelligence in the two processes proposed for analysis and observe its impact on its adoption among employees in different fields.

Keywords: artificial intelligence; human resources; Romanian companies; recruitment; selection; efficiency. (search for similar items in EconPapers)
JEL-codes: C52 O15 P42 (search for similar items in EconPapers)
Date: 2024
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