Voice vs video AI interviews: which should you use?

The short version

Both formats can run a real, adaptive interview. The difference is what the evidence contains. A voice interview produces a transcript and a recording of what the candidate said. A video interview adds their face, their room and their camera. That extra channel is sometimes useful and often a distraction, so the format should follow from what the role actually needs.

What each format captures

When voice is the better choice

The job is talking and thinking. A sales rep handling objections, a support lead calming an escalation, an engineer explaining a design choice: all are judged on what they say. Voice keeps the evaluation on that.

You care about structure. A voice interview reduces the temptation to judge things that have nothing to do with the job, such as a background, the acoustics of the room, or a webcam angle. What gets scored is the answer.

Candidates are busy or mobile. Many strong candidates are employed and interview in a break or after hours. A microphone and a link is a smaller ask than a lit, quiet room on camera.

You need hands-on work.Voice does not mean audio-only. In EmployLabs, Naira’s live voice interview can put a document, code or a code repository on screen, and candidates can edit code in an in-browser editor while they talk it through; their edits are saved with the session.

When video is the better choice

On-camera presence is the job. Broadcast, video-first customer roles, some teaching and public-facing roles: if the role is performed on camera, seeing the candidate on camera is relevant evidence.

Your process already relies on visual review. Some regulated or client-facing processes require a recorded visual interview. If so, use video and write down exactly which visual criteria are allowed to count.

If neither applies, the camera adds setup and noise without adding job-relevant signal.

Fairness and consistency

Whatever the format, two rules matter more than the medium.

Score only what the rubric names. If the rubric does not include eye contact, eye contact should not move a score. Voice makes this easier because there is less non-rubric information to leak in.

Make every score checkable.A hiring manager should be able to trace any rating back to the moment that justified it. In Naira’s reports, every piece of evidence is tied to a numbered candidate turn and stores the candidate’s exact words; a quote the candidate never said is removed by code, and a rating left with no supported quote is withdrawn.

Speech recognition is also imperfect, and that is a voice-specific risk worth asking any vendor about. EmployLabs transcribes the candidate’s own audio channel a second time, and a grammar or fluency fault is kept only where the second hearing has the same words around it. A fault the second hearing does not confirm is dropped, and a dropped grammar fault is counted as unclear audio rather than held against the candidate.

The camera adds information. The question is whether any of it belongs in the rubric.

What candidates experience

The format shapes completion. With voice, the candidate’s checklist is short: a quiet spot, a microphone and the link. In EmployLabs, the candidate opens the link, confirms their email on the page and joins. The invite stays open for 14 days, with reminders on days 1, 3 and 12. If the call drops, the candidate comes back into the same interview at the part they were in, with the time they lost added back; that place is held for 24 hours.

Video asks more: camera on, a background they are comfortable sharing, often a stronger connection. For some candidates that is trivial; for others it is the reason they do not finish. The candidate side is its own subject: candidate experience when the recruiter is AI.

Language and communication

If spoken communication is part of the role, measure it explicitly rather than letting it colour every other score. Naira interviews in English, and the report has a separate communication section that levels spoken English on the CEFR scale, one level per criterion, with the overall level computed from them. It is never a rubric dimension and never a must-pass rubric, so a strong engineer with a modest level is not marked down on engineering; a role that needs a particular level sets it as a separate requirement.

A simple way to decide

1. List the three to five things the role is judged on.
2. For each, ask: can I judge this from what the person says and does on screen?
3. If yes for all, use voice. If one genuinely requires seeing the candidate, use video for that role and keep voice elsewhere.
4. Whatever you choose, keep one plan per role. In EmployLabs, each role has one current interview plan, and a candidate’s session copies it at invite, so people invited together are measured the same way.

Three roles, three choices

Account executive. The job is conversations: discovery, objections, closing. A voice interview with a role-play in which Naira plays the buyer tests exactly that. Video adds nothing the buyer would see on most sales calls and plenty that could bias a reviewer. Choose voice.

Backend engineer. The job is reasoning about code and explaining trade-offs. A voice interview that shows code on screen and lets the candidate edit it while talking gives you both the thinking and the work. Choose voice.

On-camera presenter for a product video team. Presence on camera is part of the output. A short video segment is relevant evidence here, scored against criteria you wrote down in advance. Choose video for this role, and keep the rest of your hiring on voice.

For what a voice interview can and cannot measure once you have chosen it, read what a voice AI interview can measure; for the term itself, what an AI interviewer is.