Meta has previewed the Personal Agent Protocol, an open standard for interactions between consumers' AI agents and businesses. NiCE is co-developing the protocol with Meta, Sierra and other industry partners.
The proposal outlines how a customer's personal AI agent can find a business, authenticate itself and act on the customer's behalf. It offers an early indication of how companies may need to handle a growing volume of requests initiated by software agents rather than people.
According to NiCE, the standard is intended to address a series of operational questions for customer service teams, including how businesses verify which customer an agent represents, what the agent is allowed to do and how those interactions are managed across automated systems and human staff.
It also points to a shift in demand patterns. Rather than reducing service volumes, personal agents could increase them by pursuing tasks customers might otherwise abandon, such as repeated follow-up questions, refund requests or booking changes.
"Personal AI agents have endless time that consumers don't, and that brings a new era of growth for customer service. Customers' agents can sign in, ask follow-up questions on their behalf and get to resolution faster, which means more demand, more persistence and higher expectations. An open standard is how that demand reaches businesses with trust, and NiCE is proud to shape what comes next alongside Meta and others. Companies that compete every day agreeing on a standard so customers and enterprises both benefit is the industry at its best. Personal agents bring customers to the door, and resolution brings them back," said Scott Russell, Chief Executive Officer, NiCE.
How It Works
Under the proposed approach, a company would publish information at a known digital address telling personal agents where to sign in and which interfaces they can use. The protocol is designed so an agent can discover that information in a single request before continuing the interaction across application programming interfaces, web pages or conversational channels.
NiCE said the model also relies on customer-specific authentication tokens, with access limited according to the business's own rules. That structure is intended to let companies decide which personal agents they will accept, what those agents may do and when a person should take over a case.
Philipp Heltewig, Chief AI Officer at NiCE, said the protocol creates a common language between a customer's software agent and a company's systems.
"Personal agents already work for consumers, and today a customer's agent and a company's agent share a common language. When a customer's agent arrives with a goal, like a refund or a rebooked flight, the business's AI agent checks who it represents and what it is allowed to do, then works the request to resolution using the systems the business already runs on. When the case needs judgment, a person joins the same conversation with the full context, and every reply says who is responding. That is AI agents and people working as one crew, with clear jobs, shared context and a clean handoff. Enterprises decide which agents they serve, what access those agents get and when a person steps in, and now the conversation turns to what we build with it," said Heltewig.
Operational Pressure
For contact centre operators and IT teams, the prospect of machine-driven customer requests raises questions not just about access, but also scale. Traditional service models have been built around human behaviour, where delays, drop-offs and limited persistence naturally constrain demand.
Personal agents could change that pattern by sending requests at machine speed and continuing interactions without the time limits of a human customer. That would require businesses to think not only about external connections to personal agents, but also about internal routing between AI systems, workflows and staff.
Neeraj Verma, Vice President, Agentic AI, NiCE, said the proposed design aims to keep those interactions consistent while preserving business control.
"What I like about the Personal Agent Protocol is how much it solves with a simple design. A company publishes one document at a well-known address that lists its sign-in endpoints and interfaces, so an agent finds everything in a single request. Each personal agent gets its own token for each customer, with access scoped to what the company allows, and that same token works across APIs, web pages and conversations, so the experience stays consistent from first request to resolution. Every reply says whether an AI agent or a person is responding, and when a case calls for judgment, a person joins the same conversation with full context. Enterprises keep control throughout: they set which agents they serve, what access those agents get and when a person steps in," said Verma.
The initiative comes as businesses across customer service, digital operations and enterprise software examine how personal AI assistants could change online interactions, particularly in sectors where identity, permissions and audit trails are central to the transaction.
For companies preparing for that shift, the protocol suggests the challenge will extend beyond opening a technical connection. They will also need systems that can distinguish between customers, agents and staff at each stage of an interaction, while handling a potentially much higher volume of service requests than today.