Before a voice agent answers your phones

All Stack Labs, 12 October 2026

Many calls to businesses never reach a person. Invoca, which tracks calls for its business customers, found that only 56% of callers reach a person. Quo, a business phone provider, looked at 16.7 million missed calls and found that about 69% did not get a callback within 48 hours.

A voice agent closes that gap. It picks up every call, answers questions, books the appointment and writes it all back to your systems. Getting one to do that reliably, on real calls, is harder than the demos suggest.

Fast enough, and patient enough

People are fast. A study of conversations in ten languages found the average gap before an answer to a yes or no question was about 200 milliseconds. No phone agent matches that yet. Twilio publishes a target of about 1.1 seconds end to end, and calls it a starting benchmark rather than the best possible.

Speed is only half of turn-taking. The agent also has to know when the caller has finished. LiveKit describes an older model that decided a caller was done after each digit of a phone number. Its newer model cut false interruptions overall by 39%. An agent that interrupts a caller reading out a card number makes them start again.

Where voice agents fail

Sierra, which builds customer service agents, tested voice agents on real tasks with realistic audio: background noise, varied accents and callers who talk over the agent. By April 2026, the best agent on its leaderboard completed 67% of tasks. Their example failure will be familiar to anyone who has run a phone line: street noise and an unfamiliar accent throw off the transcription, and the identity check fails.

The quiet failures are worse, because they look like success. Roark, which tests voice agents, describes a scheduling agent that checked availability in UTC instead of the caller's local time. As they put it, "the agent sounded fine, the tool call succeeded, and the appointment was wrong." Common causes:

Time zones. The caller, the server and the calendar can each be in a different one.
Stale availability. The agent offers a slot someone booked a minute ago.
Invented answers. A price or a policy the agent was never given, said with confidence.
No way out. A caller who needs a person and cannot reach one.
Half-written records. The call went well, and nothing reached the CRM.

The rules that apply

This is not legal advice, and the details depend on your state and your industry. These are the questions to settle with your lawyer before launch:

Calling out is different from picking up. In February 2024 the FCC ruled that AI-generated voices count as artificial voices under the Telephone Consumer Protection Act. AI calls to consumers need prior express consent, and written consent for telemarketing. An AI callback to a missed caller is an outbound call.
Recording needs consent. Federal law needs one party to agree, but around a dozen states, including California, Florida, Illinois, Pennsylvania and Washington, require everyone on the call to agree. Most voice agents record and transcribe, so say so at the start.
Some states want the AI disclosed. Since January 2025, California has required health care providers that use AI to generate patient messages about clinical information to include a disclaimer, spoken at the start and the end of a call, along with how to reach a person. It does not cover scheduling or billing, or messages a licensed provider has reviewed. Utah requires disclosure when a consumer asks, and Texas requires it of state agencies and health care providers.
Health data needs a BAA. If the agent handles patient information, every vendor that stores it, recordings and transcripts included, is a business associate under HIPAA and needs a business associate agreement.

Test it before it takes a real call

A voice agent should pass a test suite before it reaches a customer, and keep passing it after every change. OpenAI's guide to evaluating real-time voice agents sets out the stages: scripted single turns first, then real noisy phone audio, then full simulated calls against mocked tools. Every failure in production becomes a new test. And keep a person listening: the same guide suggests reviewing 1 to 5% of sessions end to end.

Run each scenario more than once. Sierra's earlier research measured whether an agent succeeds on every repeat of the same task, and found reliability falls sharply as the repeats add up. A caller does not care that the agent usually gets it right.

Then track the numbers the business cares about: calls answered, tasks completed, transfers to a person, and bookings that landed correctly in the calendar.

What it takes

A voice agent that sounds good in a demo is easy to build. One that books the right slot in the right time zone, hands off when it should, follows the rules for your state and writes everything back to your CRM takes engineering. That is the part we build, and we have built thousands of agents and voice agents.

Before a voice agent answers your phones.