AI Voice Agents: What They Can Do Today

Most questions about AI voice agents are really one question: what happens on a live call, in front of a customer who is not in a demo. Contact centre and BPO managers in the Gulf and the Levant have heard enough promises. What they need is the operational list. Which calls does it take, what is it allowed to say, what does it do with a booking, when does a person get involved, and how fast can it be stopped.

This guide answers those questions for the DialerBee AI voice agent as it works today. Two voices are available, Layla for the female voice and Moaz for the male one, and Arabic is handled as dialects rather than as one flattened language, so a Gulf caller and a Levantine caller both hear something local. Everything below is a capability the platform has now, with the setting that controls it named beside it.

Where the agent sits in your call flow

The agent is not a separate product parked outside the contact centre. On the inbound side, every number lives in a DID inventory, and each number points at a routing target: a queue, a named user, an IVR flow, a campaign, or an AI voice agent. Pointing a number at the agent is a change to that one row. You can select a batch of numbers and change the target for all of them at once, and export the whole inventory to CSV when a client asks what their numbers do.

That matters more than it sounds. It means you can start with one overflow number, or one after-hours number, rather than moving the main line. If the result is not what you expected, you point the number back at the queue and the experiment is over.

On the outbound side the agent runs as an AI campaign against a contact list, using the same list and pacing machinery your human campaigns use, and it places AI callbacks of its own so a promise made on a first call is kept without occupying a seat.

What it says, and what it will not say

A voice agent is only useful if what it says is true. Answers come from a knowledge base you upload, retrieved by semantic search, so the opening hours, the policies and the service descriptions are your documents rather than a plausible guess. Change the document and you have changed what the agent knows, without rewriting a script.

Prices are stricter. The price-truth guard means only prices in your catalogue can be spoken. That single rule removes the failure that matters most in collections, retail and clinic bookings alike: a number a customer will hold you to afterwards. Guardrails sit around the rest of the conversation, and barge-in means the caller can cut in and be heard immediately instead of waiting for the agent to finish a sentence.

Appointments: book, reschedule, cancel

Booking is where an AI voice agent either earns its place or becomes a message-taking service with better grammar. The agent checks free-busy on the connected calendar before it offers a time, then books, reschedules or cancels on the call, quoting only catalogue prices.

Behind that sit the parts that make the diary trustworthy. DialerBee syncs with Google Calendar and Microsoft 365 at organisation scope and to each agent's own calendar, with change notifications, so a slot taken elsewhere does not stay bookable. The service catalogue carries each service with its duration, the resources it needs and its price. Capacity rules are applied at booking time, so a service that is full refuses the booking rather than being double-booked and untangled later.

Reminders then go out over SMS, WhatsApp and email on the policy you set, with an ICS attachment where the channel carries one, and a messages-sent report tells you what actually left the platform. A no-show is a different conversation when you can see whether the reminder ever went.

Handing the call to a person, and what is left behind

The agent hands off to a person. Design the conversation so that it does: a complaint, a payment dispute, an unusual request or a caller who simply wants a human should reach one, and the handoff should be a designed branch rather than an accident at the end of a loop.

Every AI call leaves a result behind: the recording, the transcript and the outcome, pushed into the CRM so the AI call sits in the same customer history as the human ones. That is also what makes review possible. AI call results are reportable the same way human calls are, and AI usage and billing are reported per tenant, which is the number you need before you resell the platform to a client.

After the call, the follow-up goes out on SMS or WhatsApp, matched to the voice the caller heard, so the message and the call sound like one conversation rather than two systems.

The limits you set before the first call

The honest framing for an AI voice agent is not autonomy. It is a bounded operator that does a defined job inside settings you choose in advance. Those settings exist as product controls, not as promises.

The kill switch is the control supervisors ask about first, and rightly. Stopping AI calling should be something a supervisor does in the console at the scope they choose, not a support ticket someone answers in the morning.

Building and proving the agent in Agent Studio

You build the agent yourself. Set the persona and the role, choose Layla or Moaz as the voice, upload the documents the agent answers from, and start from one of 17 industry packs so the first version already knows the shape of a collections call or a salon booking. Flow profiles decide how the conversation is structured, so the same knowledge can serve an agent that qualifies and an agent that only confirms.

Then prove it with your ear. Place a test call and listen to what the agent actually says, because a transcript of the intended script tells you nothing about pacing, pronunciation, or how a sentence lands in Arabic. When you are satisfied, publish. Every publish is a version, promoting one is a deliberate step, and rollback is there for the day a change turns out worse than yesterday's. If two wordings are being argued about, run an A/B experiment on live traffic and let the result decide.

Frequently asked questions

Can an AI voice agent answer our main inbound line?

It can, because every inbound number in the DID inventory routes to a queue, a user, an IVR flow, a campaign or an AI voice agent. Most teams start with an overflow or after-hours number instead, listen to the recordings for a week, then widen the scope. Changing the routing target back is a one-row edit.

Can it quote a price?

Yes, but only a price that exists in your service catalogue. The price-truth guard exists so the agent cannot invent a figure a customer will hold you to later. If a price is not in the catalogue, the conversation goes another way rather than producing a number.

Does it really book appointments, or just take a message?

It books. The agent checks free-busy on the connected calendar, then books, reschedules or cancels during the call, and capacity rules refuse a booking for a service that is already full. Reminders then go out on your policy over SMS, WhatsApp or email.

What happens when the caller wants a human?

The agent hands off to a person. Treat that as a designed branch of the conversation rather than a fallback, and decide in advance which cases go straight to a human: complaints, disputes, anything sensitive, and any caller who asks twice.

How do we stop it if something goes wrong?

Kill switches, at the scope you choose: one agent, one campaign, or all AI calling, from your own console. Alongside them, number exceptions list numbers the agent must never dial, and capacity and governance settings cap what it may consume before it places a call.

Does it handle Arabic properly?

Arabic is handled as dialects rather than as one flattened language, with Layla and Moaz as the voices, and the follow-up message is written for the same audience. The only acceptance test that counts is a test call you listen to in the dialect your customers actually speak.

Related reading

• AI Voice Agent
• Agent Studio
• Appointments and Reminders
• Inbound Contact Center