AnthropicAnnouncement
Seoul becomes Anthropic's third APAC office
Summary
Anthropic plans to open an office in Seoul in early 2026, making it the company’s third Asia-Pacific location after Tokyo and Bengaluru as it expands operations in Korea. Korean users rank among Claude’s top five globally for total and per-capita usage, while Asia-Pacific countries account for more than a quarter of Claude Code users and weekly users in Korea have grown sixfold in four months. Anthropic attributes the expansion to regional momentum, including more than tenfold run-rate revenue growth in the past year and an eightfold increase in large Asia-Pacific business accounts; it also points to Korean deployments such as Law&Company’s legal assistant and SK Telecom’s customer service model. The Seoul team will support Korean enterprises and startups, work with government, research, and industry partners, and align with Korea’s strategy for responsible AI development and deployment.
Context
Anthropic is expanding its global operations into Korea amid strong Claude adoption, rapid Claude Code growth, increasing large-business accounts across Asia-Pacific, and Korea’s stated ambition to become a leading global AI development hub.
Approach / What changed
Anthropic will establish a Seoul office in early 2026, build a comprehensive local team, meet with Korean customers and partners, and work with government agencies, research institutions, and industry partners on responsible AI development and deployment.
Takeaways
Seoul will be Anthropic’s third Asia-Pacific office after Tokyo and Bengaluru, with operations planned to begin in early 2026.
Korean users rank in Claude’s global top five for total and per-capita usage; weekly Claude Code users in Korea have grown sixfold in four months.
Law&Company uses Claude for an AI legal assistant, while SK Telecom used it to create a custom AI customer service model described as a telco industry blueprint.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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