The hiring world is undergoing a greater transformation than ever before, driven by the touch of technology. Many organizations have already begun setting aside traditional interview methods in favor of AI-powered voice assistants. So how are candidates responding to this radical change?

A field study conducted by Jabarian and Henkel in 2026, involving a full 70,884 candidates, presents data that challenges all preconceptions on the topic. This massive study proves that AI is fundamentally changing the interview experience. But there is a critical strategic detail here: AI only manages the information-gathering stage — final hiring decisions are still made by human managers. This "human-in-the-loop" model combines the power of technology with human judgment.

Why do candidates prefer AI interviews?

Although many assume candidates would always prefer speaking with a human, Jabarian and Henkel's data paints an entirely different picture. A surprising 78% of candidates who were given the choice preferred AI over a human interviewer. The key reasons behind this decision include:

• Lower stress and comfort: Research findings show that candidates find interviewing with AI far less stressful and more "relaxing."
• Flexibility: AI offers candidates the flexibility to schedule appointments 24/7 and complete interviews whenever they choose.
• Negative sorting: The data also reflects an important risk: candidates with lower language and analytical test scores were more inclined to choose AI. This "negative sorting" phenomenon stands out as a factor that HR strategists must consider when designing screening processes.

AI's impact on job start rates and retention

AI interviews don't just make candidates more comfortable — they also directly improve hiring outcomes. According to data from Jabarian and Henkel's study, AI interviews show the following results:

• Candidates interviewed by AI are 12% more likely to receive a job offer.
• These candidates show an 18% higher rate of actually starting the job.
• AI-selected candidates demonstrate 18% higher retention rates in the first month.
• Research results show that candidates who went through AI-powered interviews exhibit 17% higher retention in the second month, 16% in the third month, and 17% in the fourth month (though these differences lose statistical significance in later months as sample sizes decrease).

A fairer process: Reduced discrimination

One of AI's greatest contributions to hiring is objectivity. According to the research data, the reported rate of gender-based discrimination in AI interviews is 3.30%, compared to 5.98% in human interviews. In other words, AI nearly halves the perception of discrimination in interviews. Linguistic details underlie this success: AI achieves a more "sustained conversational exchange" from candidates and minimizes "backchannel" responses (like "uh-huh") that human interviewers frequently use, which can disrupt a candidate's flow or signal bias.

Flexible yet better performance

To understand how AI improves interview quality, we need to look at the concept of "controlled variance." This technology doesn't lock the interview into an entirely mechanical script — instead, it remains responsive to the candidate's answers, flexing while never departing from the organizational framework. Process efficiency breaks down as follows:

• Guideline compliance: AI performed better than the range of 83% to 100% achieved by human interviewers in following organizational interview guidelines.
• Structured consistency: While AI interviews are more structured, they remain highly responsive to individual candidate responses.
• Consistent efficiency: Satisfaction and performance metrics such as duration for candidates who went through AI interviews remain on par with those from human interviews. In other words, quality improves without sacrificing efficiency.

AI is no longer just a cost-saving tool in hiring processes — it is a strategic force that improves candidate-job matching quality. But there are also "human" obstacles to this transformation. The research shows that 36% of HR professionals harbor a "recruiter bias" against the technology, predicting that AI-selected candidates will perform worse. Yet the data proves these concerns to be unfounded.

Of course, the process is not flawless. Technical glitches occur in 7% of interviews, and 5% of candidates refuse to speak with a machine. Still, the 78% preference rate and rising retention data point to the direction of the future.

Companies adapting to this transformation appears to be not just a technology investment, but also a responsibility to build a fairer and more efficient working world.

References

• Jabarian, B., & Henkel, L. (2026). Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews. University of Chicago & Erasmus University Rotterdam.