Meta is making a major push into consumer AI with Muse, a personal AI agent designed to handle tasks on behalf of users. The company showcased Muse at its annual Connect event, signaling that Meta wants AI to become part of everyday digital life across its platforms and devices.
But while the technology may be impressive, one major question remains: will people trust Meta enough to give an AI agent access to their most personal information?
That question came up during a recent episode of the Equity podcast, where Kirsten Korosec, Sean O’Kane, and Anthony Ha discussed Meta’s AI strategy and how Muse compares with the direction being taken by companies such as OpenAI and Anthropic.
Meta Is Taking a Different AI Path
Much of the AI industry is increasingly focused on enterprise customers, coding tools, and businesses willing to spend heavily on advanced AI systems.
Meta appears to be taking a different route.
Instead of concentrating primarily on enterprise applications, the company is positioning Muse as a consumer-focused AI assistant that could eventually become part of people’s everyday routines.
That approach fits naturally with Meta’s existing products. Facebook, Instagram, and WhatsApp already have enormous consumer audiences, giving the company established channels through which it can introduce AI features.
Rather than competing directly with every enterprise-focused AI product, Meta may be looking to make AI more deeply embedded in consumer experiences.
Muse Can Already Do Some Surprisingly Useful Things
Sean O’Kane tested Muse and found that it was capable of doing more than simply answering questions.
One of the suggested features encouraged him to check for unclaimed funds. He followed the suggestion and discovered that he actually had money waiting for him.
The experience resulted in a check being sent to him, making the AI useful almost immediately.
However, O’Kane also pointed out the limitation: finding previously unclaimed money is essentially a one-time task. Once it has been completed, there may not be much reason to repeat it.
The bigger opportunity would be for Muse to handle recurring tasks such as reviewing financial accounts, identifying unnecessary subscriptions, detecting duplicate charges, or helping users manage their digital services.
That’s where the biggest challenge appears.
The Trust Problem
For Muse to become a genuinely useful personal assistant, users would potentially need to give it access to sensitive information.
That could include email accounts, financial information, subscriptions, calendars, messages, and other personal data.
And that’s where Meta faces a difficult trust question.
O’Kane said one reason he was initially willing to experiment with Muse was that the application didn’t immediately connect him to his existing Facebook, Instagram, or Threads information.
Instead, it initially treated him more like a new user.
That separation made the experience feel less intrusive. But as Muse becomes more personalized, the system increasingly encourages users to connect additional information so it can better understand them.
For a personal AI agent, that creates a fundamental trade-off: the more information the AI has, the more useful it can potentially become—but the more users need to trust the company operating it.
Meta’s Business Model Adds Another Layer
There is also a broader concern surrounding how personal information fits into Meta’s business.
Meta generates much of its revenue through advertising, meaning its relationship with user data is fundamentally different from that of some companies whose primary businesses are hardware or software subscriptions.
That doesn’t automatically mean users cannot trust its AI products, but it does create a question about how comfortable people will be giving a Meta AI agent access to highly sensitive information.
Apple, for example, has also been expanding what its AI-powered Siri can do on devices. For some users, the company’s hardware-focused business model may make them more comfortable allowing an assistant to interact with personal information.
The difference in business models could therefore become an important factor as AI assistants become more deeply integrated into people’s lives.
Muse’s Biggest Test May Not Be Technology
Muse appears capable of performing useful tasks, and Meta has an obvious advantage in reaching consumers through its existing ecosystem.
But becoming a daily personal assistant requires more than impressive demonstrations.
Users need a reason to keep coming back, and they need to feel comfortable giving the AI access to increasingly sensitive parts of their lives.
For now, Muse has demonstrated some interesting capabilities, including finding forgotten money and handling consumer-oriented tasks. Whether those features develop into something people rely on every day may ultimately depend less on what Muse can do and more on how much personal information users are willing to let Meta’s AI access.
