Meta Platforms’ AI personal assistant ‘Muse’ hits 10 million downloads just 40 days after launch [Global AI Briefing]
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- 2026-10-21 08:43:00
- Updated
- 2026-10-21 08:43:00
The industry is closely watching as competition among AI services moves beyond vying over model performance and into a new phase focused on rapidly attracting users and becoming part of their daily lives.
TechCrunch, a U.S. information technology (IT) publication, reported on the 20th (local time), citing data from market research firm Sensor Tower, that Muse, launched on September 8 (local time), had recorded 10.9 million cumulative downloads worldwide. Downloads in the United States accounted for 10.2 million.

The rapid growth of Muse is thought to be due to users of Meta Platforms’ existing platforms.
Meta Platforms services such as Facebook, Instagram and WhatsApp have a combined 3.6 billion daily users, and Muse is drawing them in as users.
According to Sensor Tower, the share of Meta Platforms’ U.S. advertising spending devoted to promoting Muse rose from 23% in September to 39% in October.
Muse also had a higher user retention rate than competing AI services.
Sensor Tower estimates that among Muse users in the United States, 30% were still using the app seven days after installing it, while 23% were using it after 14 days.
By comparison, OpenAI’s ChatGPT and Anthropic’s Claude had average retention rates of just 19% after seven days and 16% after 14 days.
Muse is a personal AI agent that goes beyond answering questions like a chatbot: it can send emails on users’ behalf, book travel and help with shopping.
In South Korea, a government-led consortium formed by SK Telecom Co., Ltd. (SKT), KT and Kakao Corp. is developing the personal AI assistant service ‘MOAI’ and preparing to launch a beta this month.
Industry observers say that securing users from existing platforms—a factor cited as the secret behind Meta Platforms’ rapid market adoption—is essential to the success of ‘MOAI.’
The point is that the ability to attract users, encourage repeat use and maintain trust is just as important as building high-performing AI models.
[email protected] Lee Gu-sun Reporter