Anthropic Launches AI Interviewer

Anthropic just announced Anthropic Interviewer, an AI-moderated interview tool they used to run around 1,250 in-depth interviews with professionals about how they use AI at work.

Read that again: one of the most advanced AI labs in the world is now using an AI interviewer to understand its own users and market.

This isn’t a side project or a gimmick. It’s a clear signal about how serious teams will run research from now on. If you’re still relying on a quarterly NPS survey and a handful of manually moderated interviews to guide product, CX, or employee decisions, you’re operating with less information than you could have—and less than your competitors soon will.

What Anthropic Is Really Saying (Even If They Don’t Spell It Out)

On the surface, Anthropic’s post is a story about “AI at work.” Underneath, it’s a story about operations.

They built an AI interviewer powered by Claude, pointed it at three audiences (general workforce, creatives, scientists), and had it run 10–15 minute adaptive interviews with over a thousand people. Then they plugged those interviews into a human-in-the-loop analysis pipeline, turned them into structured findings, and published the results.

The interesting part is not the specific topic. It’s the pattern:

AI in the middle of the research stack, not on the edges.
Qualitative interviews, but at a scale that used to belong only to surveys.
A loop from live conversations → structured themes → decisions.

They’re not waiting around for third-party reports on “AI in the enterprise.” They’re running their own AI-led research at scale and wiring it directly into how they understand their customers and market.

That’s the bar now.

Participants Didn’t Hate It. They Loved It.

A quiet but important point in Anthropic’s write-up: participants were more than “okay” with being interviewed by an AI.

Follow-up surveys after the pilot show satisfaction scores clustered at the top of the scale. The vast majority of people said the conversation captured their thoughts well and that they’d recommend this format to others.

So the old objection—“people will never want to talk to a bot instead of a moderator”—just doesn’t match what’s actually happening. Professionals don’t wake up wondering whether the person on the other side of the conversation is human or AI. They care whether the conversation is respectful, efficient, and genuinely curious about their experience.

A well-designed AI interviewer can do that. Anthropic’s data backs it up.

This Isn’t About AI Companies. It’s About How You Learn.

Anthropic used their interviewer to ask big, open-ended questions: how AI affects productivity and focus, how it reshapes professional identity, where people feel hopeful versus anxious.

Now swap “AI” for whatever is keeping you up at night:

“How is our new pricing model changing buying behavior?”
“Why are high-value customers quietly disappearing around month four?”
“What’s actually driving burnout in this region or org?”
“Why is one feature beloved by power users and ignored by everyone else?”

The method doesn’t change. You still need to define who you care about, sit them down for a real conversation, and then turn those conversations into something quantified and directional. The difference is that you no longer have to choose between “depth” and “scale.” Anthropic just showed that you can have both.

The uncomfortable question, then, isn’t “Does this work?” It’s: Why aren’t you doing it yet?

Where Perspective AI Comes In

Anthropic Interviewer is built for Anthropic’s own questions and ecosystem. You don’t have their research lab or their infra—and you don’t need it.

We designed Perspective AI to give you the same superpower inside your own organization, across product, customer experience, and employee experience.

First, we start with the decision, not just the dataset. Instead of a generic “tell us about AI” study, you tell Perspective what you’re actually trying to figure out: a drop in expansion, stalled feature adoption, a churn spike, rising turnover in one region. Our AI interviewer builds a research outline around that problem, runs adaptive interviews, and then synthesizes what it learns into assets you can use immediately—requirements docs, opportunity areas, action plans, meeting agendas, and more.

Second, we treat sampling as part of the design, not a footnote. Anthropic openly admits their study is limited by self-selection and the nature of their recruitment channels. Inside your company, you can be more precise. Perspective lets you define participant groups based on real data—plan, role, industry, usage patterns, revenue, lifecycle stage, health scores—and make sure you’re not just hearing from the loudest tiny slice of your base.

Third, we connect interviews to the stack you already rely on. Anthropic pairs Interviewer with analytics on real Claude conversations. You already have your own telemetry: product analytics, CRM, CS platforms, HR systems. Perspective links interview insights back to those records so you’re not looking at a cool one-off study; you’re looking at a living, searchable understanding of your customers and employees that sits alongside the rest of your data.

And finally, we keep researchers and operators firmly in the loop. Anthropic emphasizes that humans still design prompts, review guides, and interpret findings. We agree. With Perspective, AI handles the heavy lifting—running the interviews, drafting the first pass of the analysis—so your researchers, PMs, and CX leaders can do what only they can do: pressure-test the story, add context from the business, and decide what happens next.

What You Should Actually Do This Month

It’s easy to read Anthropic’s announcement, nod along, and file it mentally as “what frontier labs do.” That’s the wrong takeaway.

The real takeaway is that the companies shaping the future of AI are already running AI-led interviews at scale as a normal part of how they operate. You don’t need to build a foundation model to do the same with your customers, users, and employees.

Here’s a simple way to make this real in the next few weeks, not “someday”:

Pick one painful, high-stakes question you’re currently guessing about—churn, onboarding, stalled adoption, manager burnout. Define two or three segments that matter for that question. Then run a wave of AI-moderated interviews with each segment. Not five people. Dozens. Let AI take the first pass at coding themes and sentiment, have your team review and refine, and use the output to make at least one visible decision: change a flow, adjust a policy, rethink a message, redesign part of your roadmap.

That’s it. You’ve just done what Anthropic is doing—except the questions are yours, and the impact lands inside your business.

Anthropic has already decided that AI interviewers belong at the heart of how they understand their users.

The only real question left is when you’ll decide the same.