Introducing Anthropic Interviewer: What 1,250 professionals told us about working with AI

Source: Anthropic · 2025-12-04

We’re launching a new tool, Anthropic Interviewer, to help understand people’s perspectives on AI. In this research post, we introduce the tool, describe a test of it on a sample of professionals, and discuss our early findings. We also discuss future work in this direction that we can now explore with the development of this tool and through partnerships with creatives, scientists, and teachers.

Millions of people now use AI every day. As a company developing AI systems, we want to know how and why they’re doing so, and how it affects them. In part, this is because we want to use people’s feedback to develop better products—but it’s also because understanding people’s interactions with AI is one of the great sociological questions of our time.

Such a project would require us to run many hundreds of interviews. Here, we enlisted AI to help us do so. We built an interview tool called Anthropic Interviewer. Powered by Claude, Anthropic Interviewer runs detailed interviews automatically at unprecedented scale, feeding its results back to human researchers for analysis. This is a new step in understanding the wants and needs of our users, as well as gathering data for the analysis of AI’s societal and economic impacts.

To test Anthropic Interviewer, we had it run 1,250 interviews with professionals—the general workforce (N=1,000), scientists (N=125), and creatives (N=125)—about their views on AI. We’re publicly releasing all interview data from this initial test (with participant consent) for researchers to explore; we provide our own analysis below. Briefly, here are some examples of what we found:

In our sample, people are optimistic about the role AI plays in their work. Positive sentiments characterized the majority of topics discussed. However, a small number of topics such as educational integration, artist displacement, and security concerns, came with more pessimistic outlooks.

People from the general workforce want to preserve tasks that define their professional identity while delegating routine work to AI. They envision futures where routine tasks are automated and their role shifts to overseeing AI systems.

Creatives are using AI to increase their productivity despite peer judgement and anxiety about the future. They are navigating both the immediate stigma of AI use in creative communities and deeper concerns about economic displacement and the erosion of human creative identity.

Scientists want AI partnership but can't yet trust it for core research. Scientists uniformly expressed a desire for AI that could generate hypotheses and design experiments. But at present, they confined their actual use to other tasks like writing manuscripts or debugging analysis code.

This initial test explored how workers integrate AI into their professional practice and how they feel about its role in their future. We ran interviews to produce qualitative data, and supplemented them with quantitative data from surveys where participants answered questions on their behavioral and occupational backgrounds. We also had a separate AI analysis tool read the interview transcripts and cluster together emergent, overarching themes from the unstructured data—for example, on the percentage of participants who mentioned a specific topic or expressed a specific view in their interview.

We used Anthropic Interviewer to conduct interviews with 1,250 professionals. We intend for the tool to interview general Claude.ai users, but for this initial test, we sought participants working across a range of professions and engaged them through crowdworker platforms (all participants had an occupation other than crowdworking that was their main job).

Overall, the members of our general sample of professionals described AI as a boost to their productivity. In the survey, 86% of professionals reported that AI saves them time and 65% said they were satisfied with the role AI plays in their work.

One theme that surfaced is how workplace dynamics affect the adoption of AI. 69% of professionals mentioned the social stigma that can come with using AI tools at work—one fact-checker told Anthropic Interviewer: “A colleague recently said they hate AI and I just said nothing. I don’t tell anyone my process because I know how a lot of people feel about AI.”

Whereas 41% of interviewees said they felt secure in their work and believed human skills are irreplaceable, 55% expressed anxiety about AI’s impact on their future. 25% of the group expressing anxiety said they set boundaries around AI use (e.g. an educator always creating lesson plans themselves), while 25% adapted their workplace roles, taking on additional responsibilities or pursuing more specialized tasks.

In a previous analysis, we categorized AI uses into either augmentation (where AI collaborates with a user to perform a task), or automation (where AI directly performs tasks). In the Anthropic Interviewer data, 65% of participants described AI’s primary role as augmentative; 35% described it as automative. Notably, this differed from our latest analysis of how people use Claude, which showed a much more even split: 47% of tasks involved augmentation and 49% automation. There are multiple potential explanations for this difference:

Our sample of creative professionals also reported that AI made them more productive. 97% reported that AI saved them time and 68% said it increased their work’s quality. One novelist explained “I feel like I can write faster because the research isn’t as daunting,” while a web content writer reported they’ve “gone from being able to produce 2,000 words of polished, professional content to well over 5,000 words each day.” A photographer noted how AI handled routine editing tasks—reducing turnaround time from “12 weeks to about 3”—allowing them to “intentionally make edits and tweaks that I may have missed before or not had time for.”

Similarly to the general sample, 70% of creatives mentioned trying to manage peer judgment around AI use. One map artist said: “I don't want my brand and my business image to be so heavily tied to AI and the stigma that surrounds it.”

Economic anxiety appeared throughout creatives’ interviews. A voice actor stated that: “Certain sectors of voice acting have essentially died due to the rise of AI, such as industrial voice acting.” A composer worried about platforms that might “leverage AI tech along with their publishing libraries [to] infinitely generate new music,” flooding markets with cheap alternatives to human-produced music. Another artist captured similar concerns: “Realistically, I’m worried I'll need to keep using generative AI and even start selling generated content just to keep up in the marketplace so I can make a living.” A creative director said: “I fully understand that my gain is another creative’s loss. That product photographer that I used to have to pay $2,000 per day is now not getting my business.” (Note that Claude does not produce images, videos, or music—participants’ expressed anxieties are therefore about AI writ large, and not specific to Claude).

All 125 participants mentioned wanting to remain in control of their creative outputs. Yet this boundary proved unstable in practice: Many participants acknowledged moments where AI drove creative decisions. One artist admitted: “The AI is driving a good bit of the concepts; I simply try to guide it... 60% AI, 40% my ideas”. A musician said: “I hate to admit it, but the plugin has most of the control when using this.”

Our interviews with researchers in chemistry, physics, biology, and computational fields identified that in many cases, AI could not yet handle core elements of their research like hypothesis generation and experimentation. Scientists primarily reported using AI for other tasks like literature review, coding, and writing. This is an area where AI companies, including Anthropic, are working to improve their tools and capabilities.

Trust and reliability concerns were the primary barrier in 79% of interviews; the technical limitations of current AI systems appeared in 27% of interviews. One information security researcher noted: “If I have to double check and confirm every single detail the [AI] agent is giving me to make sure there are no mistakes, that kind of defeats the purpose of having the agent do this work in the first place.” A mathematician echoed this frustration: “After I have to spend the time verifying the AI output, it basically ends up being the same [amount of] time.” A chemical engineer noted concerns about sycophancy, explaining that: “AI tends to pander to [user] sensibilities and changes its answer depending on how they phrase a question. The inconsistency tends to make me skeptical of the AI response.”

91% of scientists expressed a desire for more AI assistance in their research, even if they didn’t feel today’s products fit the bill.