AI agents for customer service
AI agents now hold real customer conversations, including on the phone. Understand what they do, where they fit, and what to check before one answers your customers.
Published
The short answer
An AI customer service agent understands what a customer needs, takes action in business systems, and replies in natural language, in chat or on a live call. On voice, it depends on clear audio and fast speech recognition. The decision that matters most is not whether AI or people handle a call, but how a person can step in when judgment is needed without the customer starting over.
What an AI customer service agent is
An AI customer service agent is software that holds a conversation with a customer and works toward an outcome. It understands the request, looks up information or takes an action in a business system, and replies in natural language. Many AI agents work across chat, email, and voice.
The word agent separates this from earlier automation. A scripted chatbot or phone menu follows fixed paths. An AI agent decides its next step from the conversation, within the limits the business sets for it.
Scripted chatbot or phone menu
Follows predefined flows. Predictable, but limited to the paths someone designed in advance.
Agent assist
Supports one human agent on one call at a time with suggestions and information. The person does all the talking.
AI agent
Holds the conversation itself and completes tasks, such as checking an order or changing an appointment, within the permissions it is given.
How an AI agent handles a phone call
On a call, three systems usually work together. Speech recognition turns the caller's words into text. A language model works out what the caller means and what to do next. Text-to-speech speaks the reply.
Each step depends on the one before it. If speech recognition mishears a word because of background noise, a poor connection, or an unfamiliar accent, the language model works from an inaccurate transcript, which can lead to a wrong reply or action unless the system resolves the ambiguity. That makes audio quality a practical concern for voice AI, not only a question of how a call sounds.
Speed matters too. People notice pauses on a phone call more than in chat, so an AI agent has to recognize, decide, and speak quickly enough for the conversation to feel natural.
Why audio quality matters for voice AI agentsThree ways to put AI on customer calls
Contact centers have mostly used AI on calls in one of two ways. Sanas describes a third.
The right model depends on the work. High-volume, low-risk requests may suit more autonomy. Conversations with financial, medical, or compliance consequences call for a person who can act during the call, not only after it.
Agent assist
AI sits behind one human agent on one call at a time. The person does all the talking. The AI helps, but it does not scale them.
Fully autonomous agents
AI takes the call alone until something goes wrong. Then it hands off to a person who was not there, and the customer can end up starting over.
Supervised AI
AI agents take the calls while one person follows several live conversations and can step in or step back inside the same conversation. Sanas Supervised AI is designed for one supervisor to govern up to four conversations at once.
Explore Sanas Supervised AIWhen a person still needs to step in
A person should be able to act when a conversation reaches a decision the AI should not make alone, or when it starts to need judgment beyond routine work.
Those moments do not always announce themselves. A simple billing question can become a disputed charge. A request can reach a policy exception. Some compliance steps need extra attention.
How a person joins matters as much as when. In a conventional handoff, the person arrives without having heard the conversation, may need to rebuild the context, and the customer may have to repeat themselves. A person who has been following the conversation can act in the moment, then hand it back to the AI once the issue is resolved.
Read the AI agent governance guideWhat customers expect from an AI agent
Customers want to know who they are talking to. In Salesforce research on connected customers, most customers said it is important to know when they are communicating with an AI agent. Tell callers at the start of the call.
Customers also expect continuity. Nobody wants to explain a problem twice. Design for one continuous conversation, even when control moves between the AI and a person.
Businesses expect AI to take on more of this work. In a 2025 Cisco survey of business and technology decision-makers, respondents expected agentic AI to handle most of their customer service and support interactions with technology partners by 2028. Most also stressed combining human connection with AI efficiency.
- Disclosure: the caller knows from the start that they are speaking with AI.
- Continuity: the caller does not start over when a person joins.
- Accountability: a person is responsible for the decisions that carry consequences.
How to evaluate an AI agent for customer service
Test with your own calls and systems. A demo on clean audio with a scripted request will not show how an AI agent performs on your real traffic.
Start with one workflow
Pick a defined, high-volume request with a clear outcome, and decide in advance what the AI may and may not do.
Test on real audio
Include the accents, devices, connections, and background noise your callers actually have. Check what speech recognition heard, not only what the agent said.
Measure outcomes
Track resolution, accuracy, and how often a person needed to act, and compare them with the same workflow as you handle it today.
Rehearse the moment a person steps in
Confirm who is alerted, what context they see, how they take over, and whether the customer stays in the same conversation.
Check the record
Confirm that every AI action and every human action is recorded, and that recommendations show their sources.
Confirm where it runs
Know where audio and data are processed and which models are used, especially in regulated industries.
Further reading
Common questions
Software that holds a conversation with a customer, understands the request, takes action in business systems within set permissions, and replies in natural language. Many AI agents work across chat, email, and voice.
No. A scripted chatbot follows predefined paths. An AI agent decides its next step from the conversation and can complete tasks, within the limits the business sets.
Yes. In a common design, speech recognition turns speech into text, a language model decides the response, and text-to-speech speaks it; some newer systems process speech directly. Results depend heavily on audio quality and speed, so test with real calls.
When the conversation reaches a decision the AI should not make alone, or starts to need judgment beyond routine work, such as a disputed charge or a policy exception. A person who has been following the call can act without the customer starting over.
Many customers say it is important to know. Every Sanas Supervised AI call begins by telling the customer they are speaking with AI and that a human supervisor is in command.
Sanas's view is that AI or people is the wrong question. In a supervised model, AI agents take the calls and people govern them: one person oversees several live conversations and steps in when judgment is needed.
Keep a person in command.
See how one supervisor can govern several live AI conversations with Sanas Supervised AI.