63% of Job Seekers Have Faced an AI Interview. Most Haven’t Had a Good One Yet

NEW YORK, May 1, 2026 -- A new report by Greenhouse, the leading hiring platform, reveals that AI interviews have become mainstream, but the first wave has failed on transparency, trust, and candidate experience. Nearly two-thirds (63%) have now been interviewed by an AI, up 13 percentage points from six months ago, according to the Greenhouse 2026 Candidate AI Interview Report, which surveyed 2,950 active job seekers. Yet 38% of candidates have walked away from a hiring process because it included an AI interview, and another 12% say they would.

AI is Everywhere. Transparency Isn't
Candidates aren't rejecting AI. They're rejecting how it's being used. The majority of candidates (70%) were never clearly told upfront that AI would be evaluating them, and for one in five (21%), they only found out once the interview started. Just 18% say employers have clear AI policies, yet 57% believe disclosure should be a legal requirement.

The biggest triggers for candidates walking away from the process include: pre-recorded video interviews scored by AI with no human present (33%), companies failing to disclose how AI would be used (27%), and AI monitoring during the process (26%). Among those who completed an AI interview, 28% moved forward to the next round, while 13% were formally rejected, and 51% never heard back.

"Most AI in hiring today is making a bad system worse: more applications, less signal, and less transparency," says Daniel Chait, CEO and Co-Founder of Greenhouse. "But the process AI is being built on top of was already broken. Nobody likes writing resumes and filling out clunky job applications. Candidates want a better way to get seen, and companies want a better way to find the right people. A 15-minute conversation with an AI where a candidate can show who they are is a better front door than a keyword-stuffed resume. That's not going to come from layering AI on top of a broken process. It's going to come from building a better one."

AI Isn't Fixing Bias, Yet
Candidates report nearly identical rates of perceived bias from AI and human interviewers. One in three (36%) felt age bias from both, and 27% flagged race or ethnicity bias from both. Only 21% believe most employers are using AI responsibly.

"Candidates are telling us exactly what they want, and it isn't complicated: tell them when AI is in the room and what it's measuring. Right now, most employers are failing that test. Seventy percent of job seekers weren't told AI was involved," says Sharawn Tipton, Chief People Officer at Greenhouse. "And let's not pretend. AI isn't fixing bias, it's scaling it. Candidates can feel that, and when they walk away, it's not just a missed hire, it's a reputation problem that compounds. Until we get honest about what these tools are actually measuring and own it when they get it wrong, we're just repackaging the same problem."

Candidates Aren't Anti-AI; They Want Better AI
Only 19% want less AI in hiring. The majority want the same or more, but with guardrails: upfront disclosure (44%), a clear explanation of what AI is measuring (39%), and the option to request a human interview instead (46%). They also want proof that the system is accountable: 38% want to know that a human reviews AI's evaluation before any decision is made, and 29% want evidence that the tool has been audited for bias.

When AI interviews are done well, candidates notice: 38% came away with a more positive view of the employer. On the flip side, 34% came away with a more negative perception of the company. The gap isn't about whether to use AI. It's about whether employers are willing to build it on a foundation of transparency, fairness, and accountability, the same principles that define structured hiring.

To read the full report, visit the Greenhouse blog.

Survey Methodology
Greenhouse conducted a multi-market survey of 2,950 candidates, including 1,200 U.S.-based workers, with additional respondents from the United Kingdom, Germany, Australia, and Ireland. Unless otherwise noted, all findings cited in this release reflect U.S. respondents (n=1,200).

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