Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews

Brian Jabarian and Luca Henkel

Papers from arXiv.org

Abstract: This paper studies whether AI automation can improve organizational outcomes by reducing variance when collecting information. We conducted a large-scale natural field experiment in which 70,000 job applicants were randomly assigned to be interviewed by human recruiters or AI voice agents. In both conditions, human recruiters evaluate the interviews and make hiring decisions. Applicants interviewed by AI agents are 12% more likely to receive job offers, and these gains translate into higher job starts and worker retention, with no decline in the productivity of hired workers. Analyzing interview transcripts reveals that AI voice agents achieve controlled variance: their interviews are more structured and consistent while remaining responsive to individual applicants, which is associated with more hiring-relevant information collected. These results demonstrate that automating information collection with AI can enhance decision quality through standardization.

Date: 2026-07
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