Meta’s Muse And The Coming Agentic Internet: What Happens When AI Starts Acting For You?

When Meta launched Muse earlier this month, the interesting part was not that the company had built another chatbot. Meta’s pitch was that Muse could actually take work off a user’s hands: it could browse the web, fill forms, send emails, book travel and make purchases, while continuing to work on a task after the user has left the app. Meta describes it as a personal AI agent rather than simply an AI assistant. 

The Important Distinction

For most of the current generation of AI tools, the user still does the final work. You ask a question, get an answer and then decide what to do with it. An agent changes that relationship. You give it a task and it can decide which steps to take, visit websites, use connected services and come back when it needs your approval.

That sounds useful, and it could be. But it also creates a problem that becomes more complicated the more access we give these systems.

Can It Be Allowed To Take Decisions? What Are The Layers?

Amazon provided an early example. On September 20, Amazon began blocking Muse from accessing Amazon.com after saying that Meta had not obtained permission for the agent to shop on its platform. Amazon said third-party applications making purchases on behalf of customers should operate openly and respect the decisions of the businesses whose services they use. 

This is not simply a dispute between two technology companies. It points to a basic question about the emerging “agentic” internet: when an AI is acting on behalf of a person, who decides what it is allowed to do?

The question becomes even more complicated when the agent has access to something like email.

An inbox can contain years of conversations, work documents, financial information, travel details and personal information about other people. It can also be the recovery mechanism for almost every other online account a person has.

Meta’s own security research acknowledges this problem. Its engineers say that connecting an email account to Muse creates a particular risk because inboxes commonly contain one-time passwords, password-reset links and login links. Muse therefore filters these out rather than allowing the agent to use them to represent the user elsewhere.

This is a useful way of understanding the problem. The issue isn’t simply that an AI might “see your emails”. An agent with access to email can potentially gain information that helps it understand other parts of your digital life. The more services it is connected to, the more those pieces can fit together.

How Does This Matter For Indian Users?

India has spent years building a digital ecosystem in which people increasingly use their phones to pay bills, transfer money, book travel, shop, access financial services and interact with government services.

An AI agent entering this ecosystem could eventually be told something as ordinary as: “Pay my electricity bill, book my train ticket and renew my insurance.”

The question then becomes: how does the system know what the AI is actually allowed to do?

This is already being considered for UPI.

NPCI has been working on a framework for agentic payments that would allow AI agents to make certain UPI transactions without requiring the user to approve every individual payment. Reuters reported that the proposed Unified Agent Protocol was intended initially for smaller, routine purchases and could include identity checks, spending limits, rule-based payments and mechanisms for delegating funds. 

That is a significant change from the way we normally think about a UPI transaction. Today, the person is generally at the centre of the payment: they initiate it and authenticate it. With agentic payments, the person could give an AI continuing permission to make certain payments within defined limits.

NPCI subsequently put the proposed protocol on hold while it worked through regulatory and safety issues, according to Business Standard.

That pause is important because it illustrates what India now has to work out.

Indian Frameworks And The Potential Problems

The country already has rules covering personal data, electronic payments, cybersecurity, consumer protection and contracts. The DPDP framework, for example, establishes requirements around consent, purpose limitation, data minimisation, security and accountability when personal data is processed.

But an AI agent cuts across these areas.

Suppose an agent has access to your inbox and reads information about another person. Suppose it uses that information while making a decision. Suppose it makes a payment that you did not intend. Or suppose a malicious webpage or email manages to manipulate the agent into taking an action you never asked for.

The difficult question in each case is not simply whether an existing law can be applied. It is who authorised the action in the first place, what exactly was authorised, and who is responsible when the agent goes beyond it.

That does not mean India needs to treat AI agents as inherently dangerous. Meta has itself built several controls into Muse. It says the agent operates inside a dedicated virtual machine, has separate controls for credentials and internet access, asks for approval before sensitive actions and provides an audit trail of what it has done and plans to do. 

Those safeguards also point towards the kind of framework India may eventually need.

Should You Be Scared Of Using It? Or Should You Just Be Careful While Using It?

An AI should not necessarily have one blanket permission called “access”. There could be meaningful differences between allowing it to read, recommend, send, purchase or transfer money. The more consequential the action, the stronger the requirement for confirmation, limits and records.

For users, the same principle applies. Giving an AI access to your calendar is very different from giving it access to your email. Letting it find a product is different from letting it purchase one. Allowing it to prepare a payment is different from allowing it to make payments independently.

India therefore does not need to stop this technology from developing. But it does need to decide how digital authority is delegated to machines.

That could eventually mean clearer rules for identifying AI agents, defining their permissions, setting transaction limits, maintaining audit trails and deciding liability when something goes wrong. Payments, healthcare, insurance and government services may also need different safeguards because the consequences of an error are very different.

Muse may or may not become the AI agent that people ultimately use every day. But the shift it represents is already visible: AI is moving from helping people use digital services to potentially using those services on their behalf.

For India, that is the real policy question.

Not whether an AI should be allowed to act for us, but how much authority we should give it when it does.