Meta Says Muse Can Run Your Business.
Let’s Start With the Inbox.

There’s an email you meant to answer. It’s somewhere between a customer’s follow-up, a supplier’s revised price and seventeen newsletters you apparently needed.

An assistant that finds it, explains what needs attention and prepares a sensible reply would be useful. An assistant that confidently tells you the wrong thing about it creates another job: checking the assistant.

That tension runs through the early accounts of Meta’s Muse. In its September 29 small-business announcement, Meta invites owners to give the agent goals such as running a business or finding customers, using connections to existing apps and Meta accounts. It’s an ambitious pitch. Meta’s announcement

Before handing over the business, look at what happens with one email.

What are people actually finding?

TechRadar’s Lance Ulanoff described Muse finding a message he had missed, summarizing it and drafting a reply. The draft also offered a meeting or call he hadn’t intended to offer. He corrected it before authorizing the send. Read Ulanoff’s firsthand account

Finding the message was useful. Volunteering the owner’s calendar was a different decision. A very helpful assistant can still be a little too helpful.

Diana at AI Agents Library reported useful meeting preparation, a relevant business brief and competitor research that finished after she closed the app. She also reported Muse saying she hadn’t sent an email that she had sent. In an October 10 follow-up, she checked that a scheduled Facebook Page post went live and that Muse published to a Group she administers, with her supervision. A typo still reached a live post. Read her tests and follow-up

These accounts show useful work and errors in the same product. They don’t establish typical business savings or profit. Ordo hasn’t independently benchmarked Muse; these are published users’ experiences, alongside Meta’s documentation.

The useful shift is from doing everything to reviewing the right things

An agent can change where someone spends their attention. Instead of searching a long conversation and writing a reply from scratch, they may be able to check the source, correct a draft and decide whether to send it. That can be a good trade.

For an owner juggling customers, employees and delivery, useful preparation matters. A meeting brief ready before the call or research completed while they handle a job can remove work from an already crowded day.

But review has a cost. Count the time spent explaining the task, checking facts and fixing the output. Judge quality too: a faster reply that promises the wrong appointment is no improvement. The benefit is the work you can safely stop doing, plus any improvement in the result—not the amount of material the agent produces.

The skepticism is reasonable. Make it specific.

“I don’t trust AI” can mean several different things. Is the concern a wrong answer? Customer information leaving the business? An email sent too soon? A change nobody knows how to undo? Those are different problems, and each deserves an answer.

Reading an inbox and sending from it are different responsibilities. A first trial that only identifies unanswered inquiries has no reason to promise a customer anything. Check whether your chosen connection and settings let you keep that boundary.

Security firm Kodem’s analysis emphasizes what tools and data an agent can reach, as well as the systems that protect it. For an owner, the practical question is which records it can read and what it can do with them. Kodem’s analysis

Meta describes controls for credentials, permissions and actions, while acknowledging mistakes and attacks through information the agent reads. Those controls deserve attention. So does what you’re connecting: an inbox may contain customers’ addresses, private negotiations and information belonging to people who never chose to use Muse. Meta’s security explanation

We think skepticism earns its keep when it improves a decision. Ask for a smaller permission, check a source, require approval before sending. Dismissing every useful result because it came from AI is no more practical than approving everything because the demo looked impressive.

A restoration business makes the stakes clearer

Consider a hypothetical water damage restoration office. A customer asks when the crew will return. The schedule shows tomorrow, a technician’s message mentions a delay, and the job record hasn’t been updated.

If Muse can access the relevant tools in that business’s setup, it might gather the information and draft a response. Someone still has to confirm the delay and approve the promise made to the customer. Access to a schedule doesn’t make an old entry current.

A polished reply based on the wrong schedule is still the wrong reply. It just arrives with excellent grammar.

This is where business systems matter. The technician records the delay in the job record. The office confirms the revised visit. A named person approves the customer message. A workflow is simply that sequence of steps, people and information. Once those responsibilities are clear, it becomes easier to decide where an agent can help.

Our restoration system example shows the operating approach and its evidence limits. We’re describing a process here, not reporting a deployed Muse integration or measured restoration-company results.

Give it one useful job before giving it a department

Try a review of ten invented customer inquiry threads. Ask Muse to identify which still need an answer, link each conclusion to the source message and prepare suggested replies. Flag uncertainty instead of guessing. Keep sending outside the test.

Include two customers with similar names, a message already answered and an outdated appointment. Write down the correct result first. Then check whether the agent found the right inquiries, kept the customers separate and avoided turning an old date into a new commitment.

Record the review time, corrections and anything it missed. Decide what happens when it can’t resolve conflicting information. Repeat the task with different examples before expanding its access; one good run is a reason to keep testing.

We’d start with research, meeting preparation and drafts someone can review. Customer commitments, payments and changes to business records need a higher bar: the right authority, a visible record of the action and a way to correct a mistake.

Muse is worth taking seriously because early users have documented useful work. The sensible response is to find the assignments it earns, measure the supervision they require and expand from there. An agent has earned more responsibility when it makes the business easier to run—even after you count the work of supervising it.