Anthropic publishes 81,000-user AI interview study across 159 countries and 70 languages

What Anthropic announced on X

On March 18, 2026, Anthropic said it asked Claude users what they want from AI, what they fear, and how AI is already affecting their lives. The X post said nearly 81,000 people responded in one week and framed the project as the largest qualitative study of its kind. That matters because public AI debate is still dominated by benchmark scores, launch events, and abstract safety arguments rather than direct testimony from ordinary users at scale.

What the feature page adds

Anthropic’s writeup puts the exact count at 80,508 participants across 159 countries and 70 languages. The company says it used Anthropic Interviewer, a Claude-based interviewing system, to run structured but adaptive conversations over one week in December, then applied Claude-assisted classification plus human review to organize the responses.

18.8% of respondents were grouped under “professional excellence,” the largest single category.

13.7% were classified under “personal transformation,” and 13.5% under “life management.”

When asked whether AI had already taken at least one step toward their vision, 81% said yes.

Anthropic also says responses were de-identified before analysis and that quotes received additional manual review before publication.

Why this matters

The release is significant less as marketing and more as product-and-policy evidence. It shows that many users are not only seeking productivity, but also time freedom, cognitive support, better work, learning, health, and financial stability. That kind of qualitative signal can shape where frontier labs put product effort, safety guardrails, and public-interest research.

It also demonstrates a new research pattern: using AI itself to conduct and help analyze interviews at global scale. If that method proves reliable, labs and policymakers may be able to gather user evidence far faster than with traditional qualitative research alone. The more important follow-up question is whether findings like unmet expectations, dependence concerns, and uneven benefits actually change how AI products are built.

Sources: Anthropic X post · Anthropic feature page