What questions are asked in an AI interview?

The phrase "AI interview" makes it sound like a machine is thinking up questions as it goes. In almost every case it is not. A recruiter or hiring manager writes the question set before the job posting goes live, loads it into the platform, and the software plays it back to each candidate in the same order. The AI part is in the delivery and the scoring, not the questioning.

That single fact explains most of what feels strange about the format. Questions stay broad, because one list has to work for every applicant to the role. They avoid anything that depends on your specific resume, because the platform does not know which answers it will get. And they rarely go deeper on an interesting answer, because a follow-up would have to be written in advance too.

Two formats carry these question sets. Asynchronous video interviews record you answering into a webcam on your own time. Live AI voice or chat screens run a real-time conversation with a synthetic interviewer. The question types below show up in both.

Across platforms and industries, the same categories recur:

• Background and motivation. "Tell me about yourself." "Why this role?" "Why this company?" These almost always open the set, and they are scored on structure and relevance rather than enthusiasm.
• Behavioral. "Describe a time you handled a conflict with a colleague." "Tell me about a project that did not go to plan." These reward the STAR structure, because a scored transcript rewards a clear situation, action, and result far more than an anecdote that wanders.
• Situational and hypothetical. "What would you do if a customer asked for something outside policy?" These test judgment when you have no matching experience to draw on.
• Role-specific. A support candidate gets de-escalation scenarios, a sales candidate gets objection handling, an engineer gets a technical explanation or a short coding task. This is the group that varies most between postings.
• Logistics and screening. Availability, notice period, location or shift preference, salary expectation, work authorization. These are filters, and the platform reads them as data rather than scoring them as answers.

Practicing against the same categories in advance is more useful than memorizing any single question. The mock interview mode generates rounds from a job description so the categories match the role you applied for.

You know the questions will be ordinary. What catches people out is the delivery, and this section covers the three constraints that change how you should answer: the clock, the missing follow-up, and the retake policy.

Nearly every asynchronous platform puts a timer on each answer, and some add a short preparation window before recording starts. Because there are no follow-ups, anything you leave out is simply absent from the transcript. A human interviewer who hears a half-answer will probe for the rest; the software will move to the next question. That makes the first sentence of each answer the highest-value sentence you speak, and it makes finishing your point before the timer expires more important than polish.

Consider a customer support candidate applying to a mid-size software company. Asked to describe a difficult customer, they spend forty seconds on the background and run out of time before saying what they actually did. The transcript records a situation with no action and no result, so the answer scores as incomplete even though their real handling of it was good. Leading with the outcome would have saved the answer. Retake rules vary by employer, so check the instruction screen before you start rather than assuming you get a second attempt.

Preparation for this format is mechanical in a way that helps you. Pull the five categories above, write one specific example for each behavioral theme you can anticipate from the job description, and rehearse each aloud against a timer until you can land situation, action, and result inside the limit. Record yourself once and watch it back; the gap between how an answer feels and how it reads on a transcript is usually where the marks go.

Be clear about where a live assistant does and does not apply. Asynchronous AI video interviews record your screen and camera, and many run inside a locked-down environment, so an on-screen assistant is out of scope there and SubcueAI is not the tool for that round. Where it helps is the rehearsal beforehand and the human rounds that follow, where a real interviewer is on the other end of Zoom, Google Meet, or Microsoft Teams. More on how the formats differ is in the interview types topic, and the setup steps are on the tutorial page.