Meta Platforms’ new AI application, Muse, has quickly become a significant consumer-facing experiment for the company. Within weeks of launch it rose to the top of Apple’s iPhone App Store free charts and, according to Sensor Tower data, surpassed 2.5 million downloads; when that figure was reported on a Monday, Meta shares jumped by more than 11 percent.
What Muse can do
Meta aimed to build more than a simple chatbot: Muse is designed as an autonomous agent that can perform complex tasks on behalf of users. The app lets users give the assistant a personalized name and shows an animated character when the agent is working. Muse can do more than answer questions — it can make bookings, assemble documents, draft emails, gather information and attempt various online actions.
Real-world examples show Muse can compile a moving checklist, estimate how much packing time remains, propose items to pack, and create detailed daily schedules. In another test the system reached out to a user’s friend to coordinate an upcoming trip, then organized restaurant recommendations and alternatives into a structured Google document based on the replies.
Real web browsing via a virtual machine
A defining feature of Muse is that it uses a cloud-based virtual computer to execute tasks. That allows the system to actually browse websites, verify information and try to carry out requested actions. Users can observe these steps and intervene at any time.
The assistant can also spot obstacles during online shopping: for instance, it detected when a beauty retailer limited certain products to licensed professionals.
Functional limits and inaccuracies
Alongside the positive demonstrations, critics found shortcomings. In one test the Muse suggested venues for an evening out that had closed years earlier. In another case it promised to negotiate prices on Facebook Marketplace, but in practice could not contact sellers directly and only produced message drafts for the user.
Many retailers’ anti-automation measures limit shopping features. Amazon, for example, did not allow Muse to crawl its store. With other merchants, such as Target, the assistant reached the final stages of checkout but required the user to enter personal details and confirm the purchase.
Trust is the central obstacle
Muse often needs access to sensitive information — emails, calendars, documents and various online accounts — to perform autonomously. That requirement puts trust front and center: Meta has long faced scrutiny over data practices, particularly since the Cambridge Analytica scandal, and many users remain cautious about sharing personal data.
Surveys reflect this hesitancy. Pew Research finds roughly two-thirds of American adults think AI is advancing too quickly. Gallup reports 41 percent of Americans have little or no confidence in large technology companies. Gartner’s research indicates most consumers believe AI shopping assistants favor companies more than buyers.
Outlook for Muse
Although Muse’s launch attracted notable downloads and attention, its future as a day-to-day digital personal assistant depends on improving accuracy, reliability and user trust. The system already automates many time-consuming tasks, but it must overcome limitations interacting with live websites and the remaining accuracy issues to gain broader acceptance.
For now Muse demonstrates the potential of autonomous AI agents and has positioned itself as Meta’s most promising offering in the AI race, but widespread practical use will require convincing users that the assistant handles their sensitive data safely and performs reliably.
