Customer interviews are one of the most effective ways to understand what people actually need, think, and experience. They've also been one of the hardest research methods to scale — because every interview requires a human interviewer, a scheduled time slot, and an hour of transcription afterward.
AI-conducted interviews change that constraint. They let you send a link, have an AI guide the conversation, and get back a transcript with summarized insights — without being in the room. This guide covers what that means in practice, where AI interviews fit alongside other research methods, and how to design briefs that produce useful data.
What AI Customer Interviews Are
An AI customer interview is a conversation between a participant and an AI interviewer, conducted via voice or text. The AI follows a brief you've written — your topics, your guidelines, your tone — and adapts its questions based on what the participant says.
It's not a chatbot. It doesn't present a fixed list of questions and collect answers. It listens, follows up on interesting threads, asks for specifics when answers are vague, and moves on when a topic has been adequately covered. The experience feels closer to a conversation with a thoughtful interviewer than to filling out a form.
The participant can do it whenever they want. There's no calendar invite, no video call, no app to install. They click a link, choose voice or text, and talk.
What you get back: A full transcript with speaker labels, an AI-generated summary, and key points — ready to review as soon as the conversation ends.
What it replaces: The scheduling logistics, the live facilitation, and the manual transcription. It doesn't replace your judgment about what the insights mean or what to do with them. That's still your job.
How They Work
The mechanics are straightforward: you write a brief (the topics, tone, and context for the AI interviewer), publish it to get a shareable link, send that link to participants, and review transcripts and summaries as conversations complete. Each participant gets their own individual conversation — you can send the link to five people or five hundred.
For a detailed walkthrough with a real conversation example showing how the AI adapts and follows up, see How to Run Customer Interviews Without Scheduling a Single Call.
How AI Interviews Compare to Other Methods
AI interviews don't replace your entire research toolkit. They occupy a specific position — and understanding where they fit helps you decide when to use them versus something else.
Live interviews remain the gold standard for depth. A skilled human interviewer can read body language, improvise based on subtle cues, and build rapport that unlocks sensitive topics. If you're doing deep ethnographic research, exploring a brand-new problem space, or building a relationship where the conversation itself matters, live interviews are still the right choice. AI interviews handle the structured, repeatable conversations that don't need that level of nuance — freeing your live-interview time for the work that genuinely requires it.
Surveys excel at quantitative signal across large populations. If you need to know that 73% of users prefer feature A over feature B, a survey is the right tool. But surveys can't ask "why?" — or rather, they can, but the open-text responses are typically thin because there's no follow-up. AI interviews fill the gap when you need the qualitative "why" behind the quantitative "what," without scheduling dozens of calls.
Unmoderated usability tests (tools like UserTesting or Maze) are purpose-built for watching people interact with a product. They capture clicks, hesitations, and task completion rates. AI interviews aren't a substitute for task-based observation — they're better suited for discovery, feedback, and understanding motivations rather than measuring usability.
Open-ended survey questions are the closest analog to AI interviews, but without the adaptive follow-up. A survey asks "What's frustrating about your current workflow?" and gets a one-sentence answer. An AI interviewer asks the same question, then follows up with "Tell me more about that" or "What happened the last time that was a problem?" — and gets a story instead of a summary.
Where They Fit in the Research Toolkit
AI interviews are strongest in specific situations:
Continuous discovery. If interviews are part of your ongoing product development cycle rather than a one-off study, AI interviews remove the scheduling bottleneck that makes weekly interviewing hard to sustain.
Reaching hard-to-schedule participants. Executives, people in different timezones, busy professionals who won't commit to a calendar slot but will spend ten minutes talking when it suits them.
Gathering honest feedback on sensitive topics. Exit interviews, churn conversations, employee satisfaction — topics where participants self-censor with human interviewers because of social pressure or professional concerns. An AI interviewer has no agenda, and participants tend to speak more freely.
Customer feedback at volume. When surveys give you quantitative signal but you need the qualitative depth behind the numbers, AI interviews fill the gap without requiring proportional interviewer time.
For how the math changes when you scale from a handful of interviews to dozens, see Async Customer Interviews: How to Get Qualitative Insights at Scale.
How to Design an Effective AI Interview
The quality of your results depends almost entirely on how well you write the brief. A few principles:
Be specific about topics. This is the single biggest factor in interview quality. Compare:
- Vague: "Customer satisfaction"
- Specific: "How customers choose between our product and competitors when their contract is up for renewal"
The vague version gives the AI no direction — it could ask about anything. The specific version tells the AI exactly what to explore, which produces focused follow-up questions and actionable answers. List 3-5 topics, each one specific enough that a follow-up question would be obvious.
Write guidelines, not scripts. Tell the AI what you're trying to learn and why, not exactly what to say. "We're a B2B SaaS company trying to understand why trial users don't convert. We want specific stories about where they got stuck, not general opinions" is a good guideline. It gives the AI context to make intelligent follow-up decisions.
Choose the right tone. Conversational works for most customer research. Professional works for B2B or client needs assessments. Empathetic works for sensitive topics like exit interviews.
Write a natural greeting. The greeting sets the tone for everything that follows. Something simple and warm: "Hi — thanks for taking a few minutes to share your experience. I'm going to ask you some questions about [topic]. There are no right or wrong answers." Avoid corporate language.
Keep it focused. Three to five topics produce the best conversations. More than that and the interview starts to feel long. Less than that and you may not get enough depth. Each topic should represent something you genuinely need to learn — not something that would be "nice to know."
Iterate after your first batch. Your first brief won't be perfect. Run 3-5 conversations, read the transcripts, and adjust. You'll notice which topics produce rich answers and which fall flat, where the AI follows up well and where it misses an opportunity. The brief improves fastest when you see what the AI actually does with your instructions.
Common Concerns
"Will participants know it's AI?" Yes — transparency matters. Participants are told they're talking to an AI interviewer. In practice, most people adapt quickly. The quality of the conversation depends on the quality of your questions, not on whether the interviewer is human.
"Is the data as good as a human interview?" Different, not worse. AI interviews produce highly consistent data — the same tone, the same follow-up patterns, no interviewer fatigue. Human interviews produce richer nonverbal data and allow for improvisation. For most structured research, the AI data is as actionable as human-conducted interviews.
"How do I know the AI isn't leading participants?" The AI follows your brief's topics but doesn't push toward predetermined answers. It asks open-ended questions, probes for specifics, and accepts whatever direction the participant takes. You can verify this by reading transcripts — the follow-up patterns are visible, so any leading would be immediately apparent. The consistency advantage actually reduces interviewer bias compared to human interviews, where an interviewer's energy and interest unconsciously steer the conversation.
"Can I use this for usability testing?" AI interviews are designed for discovery, feedback, and understanding motivations — conversations where you're exploring what people think, feel, and do. For task-based usability testing where you need to observe someone interacting with a product (clicks, hesitations, task completion), you still need screen-sharing tools like UserTesting or Maze. The two methods complement each other: use AI interviews to understand the "why," and usability tests to measure the "how."
"What about people who don't like talking to AI?" Some won't participate, just as some people don't fill out surveys or don't show up to scheduled calls. Offering both voice and text options helps. In early data, response rates for AI interviews track closely with traditional interview response rates, and higher than survey response rates.
"How does this fit with my existing analysis workflow?" Each conversation produces a structured transcript and AI-generated summary. You can export these to whatever analysis tool you already use — spreadsheets, Dovetail, Notion, Miro boards. The transcripts are the raw data; the summaries are a starting point for synthesis, not a replacement for your own analysis.
"Can I use this for market research?" Yes. Market research, product discovery, customer feedback, testimonial collection, onboarding feedback, exit interviews — any conversation that follows a knowable structure.
Getting Started
You can set up and run your first AI interview in about five minutes:
- Write a brief with 3-5 specific topics and a short greeting
- Publish it and copy the share link
- Send the link to your participants
- Review transcripts and summaries as conversations complete
If you want to try it, Guided Surveys lets you set up your first interview on the free tier. Start with a small batch — five or ten conversations — and see whether the insights match what you'd expect from a live interview. That's the fastest way to know if this approach works for your research.