What AI-moderated actually means
In a moderated interview a person asks the questions, listens, and decides what to probe. In an AI-moderated interview a language model does the asking and probing, following the guide and goal you wrote, while a real participant answers. It is still a conversation; it is just asynchronous and the moderator never gets tired or forgets to ask the third follow-up.
What it is not: an unmoderated survey with an AI summary stapled on. If the tool cannot ask a follow-up that depends on what the participant just said, it is not moderating.
Where it fits in a research practice
Teams that get value from AI moderation use it for breadth and cadence, and keep human moderation for depth and discovery.
- Breadth: 30 interviews on one question in a week, across time zones, in participants' own languages.
- Cadence: a standing interview link in onboarding, after a support ticket closes, or in a cancellation flow, so evidence accumulates between research sprints.
- Hard-to-reach people: churned customers, lost deals, and busy professionals who will type for ten minutes but will not book a call.
- Depth and discovery stay human: the first five conversations on an unfamiliar problem, or anything where reading the room matters.
Quality controls that separate good from gimmick
When you evaluate a platform, or your own study design, look for these.
- Screening and consent before the first question, so you can defend who was in the sample and that they agreed.
- A goal the interviewer can see, not just a question list, so follow-ups are purposeful rather than generic "can you tell me more?".
- A cap on follow-ups per question. Unbounded probing exhausts participants and inflates drop-off.
- Editable transcripts. Voice transcription mishears; you should be able to correct a word before it becomes a theme.
- Source-linked analysis. Every theme and every sentiment score should point back to the exact passages behind it. If it cannot, you cannot cite it.
- A pilot. Run the study on yourself and a colleague; read the transcript as your participants will experience it.
Analysis you can stand behind
The risk with any AI analysis is confident summaries that nobody can trace. Insist on the chain: participant → transcript → quote → theme → report. AI User Interviews is designed around that chain: themes cite their quotes, sentiment is broken down by topic, completion and drop-off are shown per question, and the Markdown report you export carries the citations with it.
No fake logos. No invented metrics. Every claim on this page traces to the product.
Comparing platforms
The category now spans enterprise suites with their own participant panels and sales-led pricing through to self-serve tools. If you bring your own participants and want to start today, see how we compare to Listen Labs and Outset. If you need a managed panel or video interviews, those are the right places to look.
Our pricing is published: Free plan with 5 active projects and 100 participants a month; Pro is $25 a month.