Better Together: Quantifying the Benefits of AI-Assisted Recruitment

TL;DR

This study empirically evaluates AI-assisted recruitment's impact on hiring efficiency and candidate outcomes, revealing increased selection rates and employment prospects, while analyzing selection biases and decision-making processes.

Contribution

It provides the first large-scale randomized controlled trial quantifying AI's effects on recruitment efficiency and candidate success, including analysis of selection criteria and biases.

Findings

AI increased final interview pass rate from 34% to 54%.

Candidates from the AI group had a higher likelihood of finding new jobs.

AI tended to select younger, less experienced applicants.

Abstract

Artificial intelligence (AI) is increasingly used in recruitment, yet empirical evidence quantifying its impact on hiring efficiency and candidate selection remains limited. We randomly assign 37,000 applicants for a junior-developer position to either a traditional recruitment process (resume screening followed by human selection) or an AI-assisted recruitment pipeline incorporating an initial AI-driven structured video interview before human evaluation. Candidates advancing from either track faced the same final-stage human interview, with interviewers blind to the earlier selection method. In the AI-assisted pipeline, 54% of candidates passed the final interview compared with 34% from the traditional pipeline, yielding an average treatment effect of 20 percentage points (SE 12 pp.). Five months later, we collected LinkedIn profiles of top applicants from both groups and found that 18% (SE 1.1%) of applicants from the traditional track found new jobs compared with 23% (SE 2.3%) from the AI group, resulting in a 5.9 pp. (SE 2.6 pp.) difference in the probability of finding new employment between groups. The AI system tended to select younger applicants with less experience and fewer advanced credentials. We analyze AI-generated interview transcripts to examine the selection criteria and conversational dynamics. Our findings contribute to understanding how AI technologies affect decision making in recruitment and talent acquisition while highlighting some of their potential implications.