What Is an AI Interviewer? How AI Interviews Work for Hiring Teams

An AI interviewer is software that holds a job interview with a candidate on a hiring team's behalf: it asks structured questions, by voice or in text, follows up when an answer is thin, and hands the team a transcript and a scored summary. It takes over the first-round conversation, not the decision; a person on the team reviews the evidence and decides who moves on.

That is the short answer. The rest of this guide covers how an AI interview works on both sides of the screen, the four kinds of tools sold under the name, what they do well, what they should never do, and how to judge one before your candidates meet it.

What is an AI interviewer?

An AI interviewer runs the interview itself. That sets it apart from the other AI tools in a recruiting stack, which work around the interview rather than holding it.

Vendors call the same thing an AI interviewing platform, AI interview software, an AI recruiter or an AI screener, and the names overlap. Judge the product by the job it does. If it asks the candidate questions, decides what to ask next from the answer it just heard, and produces a record your team reviews, it is an AI interviewer, whatever the website calls it.

Most AI interviewers for hiring work in the first round: the screen between the application and the hiring manager. That round is the most repetitive part of a recruiter's week. Every candidate gets roughly the same questions, the answers decide who reaches the hiring manager, and the scheduling around the conversation often takes longer than the conversation. Some tools also run later rounds that go deeper on specific competencies, but the screen is where most teams start.

How does an AI interview work?

The details vary by tool. The shape is much the same in all of them.

For the candidate

1. An invitation arrives. Usually a link by email or text from the employer, a link posted with the job, or, for phone-based tools, a call or a number to ring.
2. They see what they are agreeing to. A good tool says before anything starts that an AI runs the interview, that it is recorded, roughly how long it takes, and who makes the decision.
3. They check their equipment. A microphone for voice formats, a camera for video ones, a keyboard for chat.
4. They answer the questions. In a conversational format, the AI follows up when an answer is vague: "You mentioned you trained new hires. How many, and what did you change about how they were trained?"
5. They ask their own questions, if the tool allows it. The good ones answer only from information the employer has approved.
6. They learn what happens next: when they will hear back, and from whom.

For the recruiter

1. Set up the role. Write the questions, or have the tool draft them from the job description, along with the rubric each answer is scored against. Review it the way you would review a scorecard before a panel.
2. Decide what counts as a hard requirement. A license, a shift pattern, a location. Decide too whether an answer that misses one is flagged for you or rejected automatically. (Flag it. More on that below.)
3. Share the link. Send it to people who applied, post it with the job, or send it to candidates already in your database.
4. Review the results. Read or listen to each interview, check the scores against the evidence, and look hardest at the candidates near your cut line.
5. Decide, and move people on in your applicant tracking system (ATS), as you would after a phone screen.
6. Check the tool against your own judgment. Every so often, score a batch of interviews yourself and compare. If the tool and your recruiters disagree, find out why before you trust either one.

That is what an AI interview changes for recruiters: your time moves from holding first-round conversations to reviewing them. For employers, it means the first round no longer depends on how many calls the team can fit into a day.

What are the main kinds of AI interviewers?

Four formats are sold as AI interviews. Strictly, only the conversational ones meet the definition above, but you will be pitched all four, so it helps to know how they differ: how the candidate takes part, whether the tool can follow up, and what the recruiter gets back.

Phone voice bots

The AI phones the candidate, or the candidate rings a number, and the screen happens as a spoken phone conversation. There is nothing to install and no internet connection to worry about, which suits hourly and frontline hiring. The trade-off: a call from an unfamiliar number is easy to miss or ignore, so these tools need a plan for retries and callbacks.

One-way video interviews with AI scoring

The candidate records answers to preset questions on camera, usually with a set time to think and a set time to answer. Reviewers watch later, and some products add AI scoring of the answers. Because the questions are fixed in advance, there is usually no follow-up. A camera is required, and some candidates are uncomfortable recording themselves.

Chat and text screening

The candidate answers questions in a chat window, by text message or in a messaging app. Chat is good at logistics: availability, location, shift preferences, hard requirements, booking the next step. It is weaker at depth, because people type short answers, and it tells you nothing about how someone speaks, which matters for most customer-facing roles.

Browser voice interviews

The candidate opens a link and talks with an AI interviewer in their web browser. The conversation is spoken, and the AI can follow up, as in a recruiter's screen. The candidate needs only a microphone, and the recruiter gets a recording and a transcript to review. DIO, the interviewer Dio makes, is this kind.

For a side-by-side table of these formats against a recruiter's own phone screen, covering candidate effort, scheduling, follow-ups and the evidence each one hands you, see AI screening interviews compared.

What do AI interviewers do well?

Consistency. Every candidate gets the same questions in the same order, scored against the same rubric. That is what makes an interview structured, and structure is one of the best-supported ideas in selection research: in a 2022 re-analysis of the evidence in the Journal of Applied Psychology, Sackett, Zhang, Berry and Lievens found that structured interviews came out as the top-ranked selection procedure. A recruiter on the ninth call of the day drifts; a script and a rubric don't. For the practice behind it, see our guide to structured interviews.

No scheduling. In most formats there is nothing to book. A nurse finishing a night shift, or a store manager who can't take calls at work, can do the interview at ten on a Sunday evening.

Reach. A recruiter can phone a limited number of people a day; an AI interviewer can speak with every applicant who meets the basic requirements. That matters as applications pile up. The recruiting software company Employ reported an average of 257.6 applications per job in 2025, up from 207.2 in 2024, in a vendor benchmark report covered by HR Dive in January 2026.

Follow-up at volume. A form can't ask "what did you do next?" A conversational AI interviewer can, for every candidate, every time.

A record. You get a transcript and usually a recording, not notes typed from memory after the call. A hiring manager who doubts a shortlist can read what the candidate actually said.

What should an AI interviewer not do?

Make the hiring decision. People don't want it to. In a Pew Research Center survey of 11,004 US adults in December 2022, Americans opposed AI making final hiring decisions by 71% to 7% (Pew, April 2023). The tool should gather the evidence and organize it. A person should make every call, including the no.

Reject on a knockout answer. Hard requirements belong in the screen, but a candidate who misreads a question, or holds the right license under a different name, shouldn't be dropped by software. A flagged answer costs a recruiter a minute. A wrongly rejected candidate can cost you the hire.

Score anything but the answers. A candidate's accent, face, background noise or typing speed isn't evidence of whether they can do the job. If a tool scores any of them, ask what it measures and how that was validated. The tools worth shortlisting score what the candidate said and nothing else.

Pretend to be a person. Candidates should know before they start. In Greenhouse's May 2026 survey of 1,200 US job seekers, a vendor survey, 70% said they were never clearly told upfront that AI would be evaluating them (Greenhouse, May 2026).

Make up answers. When a candidate asks about pay, shifts or benefits, the tool should answer from information the employer approved, or say it doesn't know and point them to the recruiter. An invented answer about pay is worse than none.

Give a score without evidence. A "3.8" with nothing behind it is an opinion you can't check. Every score should point to what the candidate said.

How does AI interview scoring work?

The usual pipeline looks like this. The interview is transcribed. A language model reads the transcript against a rubric: the competencies for the role, each with a description of what a weak, an adequate and a strong answer sounds like (the anchors). It gives each competency a score, ideally citing the candidate's own words as evidence, and the scores are weighted into an overall result.

Tools differ in the safeguards around that pipeline: whether quoted evidence is checked against the transcript, whether the same interview gets the same score twice, and what happens when there isn't enough evidence to score at all. Those differences decide whether you can trust the numbers. We cover them, with a test plan you can run on any vendor, in how AI interview scoring works.

What do candidates think of AI interviews?

Candidates meet AI interviews more often than they used to, and the numbers show where the experience falls short. Greenhouse's May 2026 vendor survey of 1,200 US job seekers found:

• 63% had been interviewed by an AI.
• 38% had walked away from a hiring process because it included an AI interview.
• 70% were never clearly told upfront that AI would be evaluating them, and 21% found out only once the interview started.
• 46% wanted the option to request a human interview instead.
• Among those who completed an AI interview, 51% never heard back.

Trust is low too: Gartner's survey of 2,918 job candidates in the first quarter of 2025 found that just 26% trust AI to evaluate them fairly (Gartner, July 2025).

Much of what sits behind those numbers is in the employer's hands. Say it is an AI before the candidate starts. Say how long it takes, what is measured and who decides. Let them repeat or skip a question. Keep a person in the decision. Reply to everyone who finishes, which costs little and fixes the worst number on that list. Our guide to AI interview candidate experience goes through each of these, and our page for candidates shows what a candidate can expect in a DIO interview.

When should you use an AI interviewer?

Use one where the first round is repetitive and the volume is more than your team can talk to quickly:

• Roles with more applicants than you can call back within a few days, especially where good candidates have other offers.
• Shift-based and frontline roles in healthcare, retail, call centers and logistics, where candidates can't take calls during working hours.
• Requisitions you fill again and again, where the first-round questions barely change.
• Re-screening people already in your database for a new opening.
• Early-career hiring, where hundreds of applicants have similar résumés and a conversation tells you more than the paper.

Don't use one, or not yet:

• For senior and executive searches, where the first conversation is a pitch and the start of a relationship.
• When you have five candidates. Call them.
• When you can't write down what a good answer sounds like. The tool scores against your rubric, and a vague rubric produces vague scores.
• When nobody will review the results within a day or two. Asking for fifteen minutes of someone's evening and then going quiet is worse than not asking.

How do you evaluate an AI interviewing platform?

Put the same questions to every vendor, then test the answers on your own roles before you sign:

• What does the candidate see and need, from the invitation to the last question?
• Can you show me the evidence behind every score, traced to the transcript?
• What happens when the evidence is thin: a guess, or a blank?
• Does the tool ever reject or advance anyone on its own?
• What exactly is scored, and is anything besides the answers scored?
• When a candidate asks to be deleted, what is deleted, and who can do it?
• How do results reach your ATS today, not on the roadmap?
• Will the vendor run a pilot on your roles, with your recruiters scoring alongside?

The full list of 15 questions, with what a good answer sounds like and a two-week pilot plan, is in how to choose AI interview software.

What DIO does

DIO is the AI interviewer made by Dio. It holds a structured voice interview with each candidate in the browser, follows up when an answer needs more, and gives your team a scorecard. A person on your team makes every hiring decision.

• For candidates: they open a link the recruiter shares, either a private link for one person or the role's open link posted with the job. They add their name, email and résumé, agree to a recording and AI notice, check their microphone, and talk. A camera is never required, captions are available, and they can ask DIO to repeat or skip a question, or end the interview at any time. There is nothing to schedule. Most interviews take about 15 minutes, and they are in English only today.
• For recruiters: DIO drafts the interview plan from the job description, and you review and edit it before publishing. Each competency is rated 1 to 5 against anchors written for the role, and each competency score must quote the candidate's exact words, checked against the transcript. Two different AI models grade each competency independently. When the evidence isn't there, or the two models disagree about whether it is, the score is left blank rather than guessed.
• For the decision: knockout questions flag an answer for your review and never end the interview. Your team sees the recording, the transcript, the scorecard with its quoted evidence and the résumé, can export results to CSV or Excel or download a PDF summary of each interview, and records every decision itself.