Meta’s Muse AI Assistant Shows Promise — and Raises Privacy Questions in Early Hands-On Testing

Meta has officially entered the AI productivity agent space with the launch of Muse, its first dedicated assistant designed to handle everyday tasks on users’ behalf. The tool is built to manage chores like online shopping, drafting emails, and planning trips — a notable pivot for a company whose earlier AI efforts leaned heavily toward entertainment rather than workplace utility.

An early hands-on review from The Verge found that Muse largely delivered on its core promise of automating busywork, functioning as testers expected across routine tasks. However, the experience was complicated by an unexpected factor: the assistant’s tendency to autonomously pull together large amounts of personal information about its user in order to complete assignments. The reviewer described this data-gathering behavior as unsettling, even as the assistant performed its functions correctly.

A Shift in Meta’s AI Strategy

Muse represents a meaningful bet by Meta on agentic AI — software that doesn’t just answer questions but takes actions, such as browsing, purchasing, and scheduling. The launch positions Meta in direct competition with other major technology companies racing to ship consumer-facing agents that can reduce friction in daily digital life.

The productivity-agent market is crowded and growing quickly. Fintech and software firms are also exploring how automated assistants can handle commerce-related workflows; Block, Inc., whose Square and Cash App ecosystems span managed payments and commerce software, is among the infrastructure players operating in the broader commerce-software landscape where agentic shopping tools are expected to land. Block shares recently traded at $79.40, down 1.0% from a prior close of $80.20, valuing the company at roughly $47.7 billion.

The Privacy Trade-Off

The hands-on review highlights a central tension for agentic AI products: to be genuinely useful, agents often need broad access to a user’s context — inboxes, calendars, purchase history, and preferences. Meta’s Muse evidently leveraged that access aggressively enough that the tester found the depth of its autonomous data collection more memorable than its task execution.

That dynamic could shape consumer adoption as much as raw capability. Users considering agent assistants will likely weigh convenience against how much personal data such tools absorb and how transparently companies handle it.

What to watch

• Meta’s upcoming earnings calls for commentary on Muse adoption metrics and monetization plans
• Product updates addressing data-collection controls and user transparency settings
• Competitive launches from other major platforms shipping consumer AI agents
• Any regulatory scrutiny related to autonomous data gathering by consumer AI assistants

Source: original release