---
id: "entity-anthropic-d5"
type: "entity"
entityType: "organization"
canonicalName: "Anthropic"
aliases: ["Anthropic PBC"]
source_timestamps: ["§ When You Need the “Why” Behind the Numbers"]
tags: ["ai-company", "scale"]
related: ["concept-llm-based-interviewers", "quote-anthropic-scale", "claim-ai-resolves-research-tradeoff"]
sources: ["commercial"]
sourceVaultSlug: "hbr-seg-commercial"
originDay: 5
articleStem: "hbr-new-30-ai-scale-customer-research"
sourceUrl: "https://hbr.org/2026/04/how-ai-helps-scale-qualitative-customer-research"
sourceTitle: "How AI Helps Scale Qualitative Customer Research"
---
# Anthropic

**Anthropic** used its Claude-based **"Anthropic Interviewer"** to conduct **over 80,000 interviews with users in 159 countries and 70 languages**, demonstrating the massive global scale achievable with AI moderation.

## Contributions in this source

- Proof point for the global scale of [[concept-llm-based-interviewers]] and the tradeoff-bridging thesis → [[claim-ai-resolves-research-tradeoff]].
- Source of [[quote-anthropic-scale]].

## Canonical reference

anthropic.com; developer of the Claude LLM. Note: the exact figures (80k / 159 / 70) are **company-reported and not clearly verifiable in public documentation** — treat as an order-of-magnitude illustration.