AI voice agents now take actions on calls. Are they the right ones?

What changes when AI voice agents answer and act on the phone, and what the contact center teams getting it right do differently.

For the last couple of years, most AI voice agents on the phone have answered the likes of order status, what the opening hours are, where's my package right now, etc. Now enterprises want them to take self-service actions too as part of their wider agentic assurance strategy, such as booking an appointment, issuing a refund, or updating an account in the middle of a live call, in dozens of markets at once.

It's the step every new hire in a store goes through. In week one they can tell you the opening hours and check the stock room for your size. The cash register keys come later, earned one shift at a time, with a manager watching. A AI voice agents takes that step across thousands of calls, all at the same time.

The trade nobody should have to make

A few weeks ago our team sat down with the people leading the AI voice agent rollout at a global consumer brand. Their first customer facing AI voice agent is in pilot in one market, with dozens more planned from early next year. For now it can look things up and nothing more. Letting it process returns and update orders is penciled in for next year, once legal is comfortable.

What stuck with me was the discussion with them around their testing process. Their QA and security teams both place test calls by hand, in parallel, and there aren't enough hours in the week to rerun everything after every change. So they knowingly carry some risk, weighing the capacity they have against what could go wrong.

That's a pretty sharp team being honest about the tools in front of them, and I'll take that over a slide claiming everything is covered. It’s still a trade off, and it gets much harder to live with once that agent can issue refunds and the likes.

Why acting changes the stakes

When a AI voice agent only answers, a wrong answer is a poor customer experience that you can put right on the next call or quickly escalate to a human agent to fix. When it acts and makes decisions, the damage is done before anyone spots it. The refund has gone out, the booking has moved, or the record has changed.

We can already see this happening in the chat space. NBC Chicago reported last month about a traveler whose airline chatbot told her a $200 travel credit would last five years, when it was due to expire within months, and on another customer who posted that a question about a refund fee ended with the chatbot canceling their entire trip. On the phone it gets harder again. The AI voice agent has to make sense of a request over a compressed mobile line, a strong accent and a noisy street before it can act.

Builders are feeling the heat. AssemblyAI's survey of more than 450 voice agent builders found most are confident building agents, yet three in four report reliability barriers. Customers are feeling it too, while the brand takes the reputational or financial hit in the end. Invoca's research, covered by MarTech, found that customers hold the brand responsible nearly three times as often as the technology when an AI interaction goes wrong. Sinch's study of enterprise AI agents also found that 74% of companies had already pulled a live agent after governance problems. Add the EU AI Act transparency rules, which since August this year cover AI hotlines and voice assistants, and the bar keeps rising.

This all paints the picture to us that risk has moved from what the agent says to what it does, and the business is responsible for both.

What the best contact center teams are doing right

The enterprises handling this well are moving fast, and they share five habits.

1. They let the agent earn its permissions: Answers first, then simple actions, then money and regulated requests, with each step unlocked by evidence from real calls. It's how you'd bring on a new hire, and it keeps legal and risk on board.
2. They retest after every change: A prompt edit, a model update, a new knowledge base article or a carrier rerouting traffic can each change what a caller gets. The critical journeys run again automatically every time, so capacity stops capping how much risk gets checked.
3. They test the way customers call: Calls placed in-country from inside each market, over local fixed and mobile carriers, in the caller's language, with interruptions and background noise. A quiet lab test room shows the agent at its best. A call from Mexico City on a local mobile network in traffic shows the agent your customers actually meet.
4. They check what the agent did, as well as what it said: A friendly "that's all sorted" counts for little until the refund appears in the system of record, for the right customer and the right amount. More on that in my next piece.
5. They keep the record: Every test, every market and every change sits on file, so when the board, an auditor or a regulator asks how the agent behaves, the evidence is ready to hand over.

Remove the risk, keep the pace

I'll be fairly direct about where things stand. Nobody in this industry has every answer on testing agents that act. It’s a rapidly evolving area, but one that companies are adamant to roll out. These systems are probabilistic, and pinning down why a call failed is often harder than spotting that it did.

That difficulty has a name in IT operations: mean time to innocence. It’s how long each party takes to prove a failure wasn’t theirs. When a AI voice agent gets a refund wrong, the carrier, the contact center platform, the AI vendor and the model provider can each show their own piece working, while the caller is still waiting on the right outcome. With agents that act, every hour spent working out who’s to blame is an hour the wrong refund or booking stays live.

What we can do is what Klearcom was built on: call the deployed agent from inside 100+ countries over 340+ carriers, the way customers reach it, then score what it understood, said and did against the rules the business sets, and keep the evidence.

That's what agentic assurance looks like when agents move from answering to acting. It closes the gap between how fast the business wants to move and the risk it can accept, so speed and safety stop pulling against each other.

If your agent is about to get rolled out, I'd be glad to compare notes and how Klearcom can support you and your team.