Navigating AI in Personnel Selection: A Scenario-based Study on Applicants’ Perceptions

Czernietzki C; Märtins J; Westmattelmann D; Grotenhermen J-G; Oldeweme A; Borgstedt V; Schewe G

Abstract

AI-based systems are increasingly deployed on organizational tasks, such as personnel selection decisions. As existing research indicates that applicants generally react negatively to the use of AI in personnel selection, this study examines how organizations can mitigate adverse reactions to fully exploit the benefits of AI. To obtain robust results, we recruited an online sample of German participants (N = 1,852) and presented them with various selection scenarios. Using a between-subject design, the process stage (pre-selection vs. interview) and the degree of process automation (augmented vs. automated) were manipulated. By employing a multidimensional conceptualization of transparency, we show that disclosure and accuracy positively impact procedural justice perceptions, a strong predictor of process quality assessment. This relationship is robust across selection contexts. Results indicate that applicants prefer AI for pre-selection and as human decision support, thus offering overall insights into design choices for AI in selection, optimizing applicant reactions.

Keywords
AI; personnel selection; applicant reactions; transparency; procedural justice; process quality