Meta’s Muse is a personal AI agent that can work across connected services and take actions, not just answer questions. That can make it useful—but it also means the agent may need access to sensitive information such as email, calendars, and online accounts. Meta describes controls for permissions, approvals, training opt-outs, and data handling, but those are company claims, not an independent security audit.
What is Meta Muse?
Meta announced Muse on September 8, 2026, describing it as a personal AI agent powered by Muse Spark. The company says it can work across connected services, open a browser, fill in forms, and continue longer tasks in the background. For sensitive steps such as sending an email or making a purchase, it may ask for approval.
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At launch, Meta said Muse was rolling out in the United States on iOS, Android, and muse.ai, with support for AI glasses planned later. The Associated Press reported that the initial product was for adults 18 and older in the US. Availability and eligibility can change, so check the current app or service terms. (Meta announcement; Associated Press)
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The name covers more than the agent. In July 2026, Meta introduced Muse Image, an image-generation and editing model integrated with Muse Spark, and previewed Muse Video, a video model with native audio support. At the time, Meta said Muse Video was coming soon to creators and Meta AI. Muse Image was available in the Meta AI app and on meta.ai, in Instagram Stories in the US, and in WhatsApp in limited countries. These creative tools are distinct from the personal agent’s connected-service access and should not be treated as the same feature. (Meta AI: Introducing Muse Image and Muse Video)
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What does Meta say Muse does with your data?
Meta says each person’s Muse runs in a dedicated cloud virtual machine containing that agent and the user’s data. The company also describes a separate Sentinel process that must approve internet access, secure storage for credentials to connected services, approval prompts for sensitive actions, and an audit trail. Users choose which services to connect and what permissions to grant, and can disconnect services.
Meta says Muse conversations and virtual-machine data are not shared with its advertising systems. These are descriptions from Meta; the sources cited here do not independently verify the architecture or audit its implementation. (Meta’s Muse announcement; Meta AI Research: How We Built Safety Into Muse)
Agent activity and model training
Meta says conversations, tool calls, and handoffs between subagents—what it calls “trajectories”—can help train new model checkpoints. It says these are sanitized to remove key personally identifiable information and that users can opt out in Muse settings. Axios reported on September 25, 2026, that use for training was allowed by default and could be turned off. Defaults and menus can change, so look for the current training control in your own Muse settings rather than assuming the reported default still applies. (Meta AI Research; Axios)
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Meta also said in September that it planned to introduce Muse Confidential VM later in 2026. The proposed feature would encrypt the virtual machine with a key held only by the user, so Meta could not access it. That was a planned capability in the announcement, not evidence that it is available now. Axios also reported plans for private processing with AI glasses; the Muse privacy changes may not apply in the same way to people using Meta AI through other apps. (Meta announcement; Axios)
What controls can users check?
Meta describes several controls intended to let people limit access and use:
- Connected services: Choose which services Muse can connect to, review the permissions granted, and disconnect integrations you no longer want it to use.
- Sensitive actions: Watch for approval requests before consequential steps, such as sending email or making purchases.
- Training: Check Muse settings for the control governing whether conversations and agent activity may be used to train models.
- Learned information: Meta says users can ask Muse to forget specific information it has learned.
- Activity review: Meta says the system includes an audit trail, which can help users inspect agent activity.
These controls address different risks: disconnecting a service limits future access, while a training opt-out governs a separate use of interactions. Meta’s descriptions do not establish how every control behaves in every version or connected service; review the current permissions and settings in the product you use. (Meta announcement; Meta AI Research)
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Why privacy concerns remain
More access can mean more usefulness—and more exposure
An agent that can organize a calendar or act on an account needs more than a prompt and a reply. Depending on the task and the services connected, it may need access to messages, schedules, credentials, or other account data. The practical trade-off is that broader access can make more tasks possible while increasing the amount of sensitive information involved and the consequences of a mistaken or unwanted action.
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Prompt injection and mistakes are not solved
Meta acknowledges that prompt injection remains an open problem and that Muse will sometimes make mistakes. A separate internet-access approval process and prompts for sensitive actions may help limit damage, but they are risk controls—not a guarantee that the agent will always interpret instructions correctly or avoid unintended behavior. (Meta AI Research)
Cloud privacy depends on the actual protection in place
Meta’s planned Confidential VM feature would change who holds the encryption key, if delivered as described. Until it is available and its scope is clear, do not treat it as a present protection. More broadly, a company’s description of its security design is not the same as an independent audit or proof that no access or exposure is possible.
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People nearby raise a different privacy issue
Privacy controls over stored conversations do not settle whether people around a camera- or microphone-equipped device know they may be recorded. Axios quoted Electronic Privacy Information Center executive director Alan Butler warning that everyday devices with embedded cameras and microphones pose risks to people who do not want to be recorded or surveilled. He added, “Confidential processing doesn’t solve the problem of pushing embedded surveillance systems out into the world.” That concern is about capture and bystander consent, not just how a user’s stored agent data is protected. (Axios)
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the Muse Image controversy shows—and does not show
In July 2026, Meta withdrew a Muse Image feature that made public Instagram-account photos automatically available as references for image generation. The feature drew criticism and privacy concerns; the Associated Press reported calls for users to change Instagram settings. Meta said the feature had “missed the mark” and was no longer available.
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How to assess any personal AI agent
When deciding whether to connect an agent to personal accounts—or comparing services—check the details that determine its reach and accountability:
- Which services and categories of data can it access?
- Can it only read information, or can it also send, edit, buy, or otherwise act? Which actions require approval?
- Can conversations or actions be used to train models, and is that use opt-in or opt-out?
- Who can access stored data, and who controls any encryption keys?
- Can you inspect activity, delete learned information, and disconnect a service?
- What happens to bystanders who may be captured by connected cameras or microphones?
For Muse specifically, the answers vary by service, permission, current settings, and which announced features have actually launched. The available descriptions support these as questions to verify, not a complete independent ranking of Muse against other agents.
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