Key points
- Meta confirms Muse has exceeded 10 million users, validating earlier market data.
- Average purchase size for engaged shoppers is over $200, a high value for AI agents.
- Daily retention stands at 25% of users who set up the application.
Meta announced during its third-quarter earnings call that its AI application, Muse, has been adopted by more than 10 million users. This figure confirms estimates released earlier in the week by market intelligence firm Sensor Tower. The company highlighted that user behavior is shifting toward high-value commercial activities and personal productivity tasks.
By the numbers
- 10 million: Total confirmed users of the Muse AI application.
- 25 percent: Share of users who set up Muse and return to use it daily.
- $200: Average purchase size for engaged users shopping via the AI agent.
What the figures mean
CEO Mark Zuckerberg noted that the spending levels were surprising to industry insiders. He stated that Plaid, the financial technology provider connecting payment apps to bank accounts, had not seen similar activity on any other service. This suggests users are trusting the AI agent with significant financial transactions.
Beyond commerce, users are connecting Muse to email and calendars for personal productivity. Zuckerberg emphasized that this adoption indicates trust in the app’s security setup. The current version includes a feature called “Muse Secure VM” to protect data and privacy.
Meta plans to introduce “Muse Confidential VM” in the future. This update will prevent even Meta employees from viewing user content. The company believes it has achieved product-market fit and is now focusing on scaling the agent, increasing revenue, and optimizing compute costs.
What should you do?
Managed service providers should monitor client usage of AI agents that connect to financial or email systems. Teams usually need to verify that clients understand the data access permissions granted to these tools. Check whether existing security policies address third-party AI integrations. Ensure that logging and monitoring are active for any new applications accessing sensitive corporate data.
Operational impact
Organizations should review their vendor risk management processes for AI-driven services. IT leadership needs to assess whether current data classification policies cover interactions with external AI agents. Security teams must determine if existing controls are sufficient for applications that process financial or personal data. Communication should include clear guidance on acceptable use and data privacy expectations for staff.
Background: Personal data
Personal data includes any information that identifies you or can be linked back to you. Common examples are names, email addresses, home locations, and IP addresses. Even browser cookies and device IDs count if they can single you out from the crowd.
Read the full guide: Personal Data Examples: What Counts and How to Protect It
What to do and how to stay safe: Meta
- Review access permissions for any AI applications connected to corporate email or financial accounts.
- Monitor transaction logs for unusual spending patterns or unauthorized purchases made through AI agents.
- Verify that clients using such tools have enabled available security features like secure virtual machines.
- Once the vendor provides an update, test new privacy features in a controlled environment before broad deployment.
Step-by-step guide: Data Classification Best Practices for Enterprise Security
General security guidance from the BitShield News newsroom. It is not confirmed advice from the organisations named in this story.
Frequently asked questions
How many users does Meta Muse have?
Meta confirmed that Muse has been adopted by more than 10 million users.
What is the average spending for Muse shoppers?
Engaged users shopping via the AI agent have an average purchase size of over $200.
Will Meta see user content in the future?
Meta plans to launch “Muse Confidential VM,” which will prevent the company from viewing user content.
