Rejected Applicant Reactions to Artificial Intelligence/Human Manager‐Based Recruitment
ABSTRACT The increasing use of artificial intelligence (AI) in job recruitment has transformed recruitment practices. Little is known, however, about how applicants react to AI‐based rejection. Drawing on appraisal theory, we propose that applicants rejected by AI tend to appraise the rejection as others' responsibility, leading to negative emotions and adverse reactions against the organization. Using a person‐centered approach and mixed‐methods design in two studies, we identify four distinct profiles based on the combination of outward‐focused negative emotions (OFNE) and inward‐focused negative emotions (IFNE). Specifically, we argue and test that introducing a human manager to review AI‐based rejection can soothe rejected applicants. Our findings show that involving human touch can shift applicants' profiles, leading to better reactions toward the organization. Theoretical and practical implications for rejected applicant reactions in the context of AI‐based recruitment processes are discussed.
Authors
- Jie Cao (ORCID: https://orcid.org/0000-0001-6705-7528)
- Jinsong Li (ORCID: https://orcid.org/0000-0002-7251-2211)
- Lingjun Zhou (ORCID: https://orcid.org/0009-0003-7637-4375)
Institutions
- Shanghai University of Finance and Economics (CN)
- Minjiang University (CN)
Publication Details
- Journal
- Human Resource Management
- Published
- 2026-08-25
- DOI
- https://doi.org/10.1002/hrm.70093
- Primary Topic
- Employer Branding and e-HRM
- Type
- article
- Field-Weighted Citation Impact
- 0.00