Why AI-enabled Interviews Might Reduce Candidates’ Job Application Intention?

Despite the widespread use of artificial intelligence technologies in human resource management functions such as recruitment, how job candidates perceive and react to AI-enabled interviews remains uncertain. Integrating signaling theory and fairness heuristic theory, we proposed that AI-enabled interviews reduce candidates’ job application intention via the mediating role of procedural justice and organizational attractiveness. Utilizing an online scenario-based experiment by adopting a 2(type of industry) × 3(format of interview method) between-subject factorial design, our results indicate that AI-enabled interviews would decrease both perceived procedural justice and organizational attractiveness of applicants, thus further reducing their intention to apply for jobs. We also find the fit of industry and interview format could contribute to the functioning of AI-enabled interviews. Specifically, AI-enabled interviews are more likely to trigger desirable reactions in high-tech industries rather than traditional industries. We discuss the theoretical contributions and practical implications for organizations.