AI in call centers: what AI agents actually do

What AI does in a call center

• Answer and route

  Pick up inbound calls and send them on

• Agent assist

  Suggested replies and summaries for live agents

• After-call notes

  Records written once the call ends

• Quality checks

  Review conversations at scale

• Deflection

  Resolve simple chat and email questions

AI in call centers is not one tool. It is a set of uses that touch every stage of a contact, from the first ring to the notes written afterward.

By 2027, AI may settle 50% of service cases, up from 30% in 2025, Salesforce's service research projects. That is a vendor forecast, not a neutral measurement.

The same research says 79% of service leaders see investing in AI agents as essential to meet current demands.

How an AI voice agent handles a call

An ai call center agent listens to the caller, works out what they need and acts on it.

A scheduling example from Twilio: the system checks provider availability, books the appointment, delivers preparation instructions and sends a reminder.

The strongest setups follow a clear order. Whatever the agent cannot settle goes to a person, context included.

For the phone channel in particular, see our AI voice agent page.

Chatbots for call centers

Chatbots for call centers handle the written side of the queue: web chat, messaging and email. They take repeat questions so people can focus on harder cases.

A conversational AI call center combines chat and voice behind one set of tools. Salesforce reports that 89% of service professionals say conversational AI raises self-service resolution rates, and 88% say it speeds up resolution.

Those are vendor survey results. Customers are less sure: Five9 found 56% of consumers are often frustrated by AI customer-service chatbots.

For the written channel, our AI chatbot page covers the details.

Agent assist and after-call work

Not every use replaces a person. Agent assist works beside a live agent, suggesting answers and summarizing the conversation.

Verint reports that agents still spend roughly 3 minutes per call on after-call work, a task generative AI is well suited to remove.

A study from the National Bureau of Economic Research looked at an AI assistant for support agents.

Support staff with AI help resolved 14% more issues per hour, novices gained 34%, and experienced staff saw little change.

The same study found the assistant improved customer sentiment and employee retention.

What customers think of AI in call centers

Customers are cautious. Gartner found 64% of customers would prefer companies did not use AI for customer service. Five9 found 75% prefer talking to a human by phone or in person.

SurveyMonkey's 2025 numbers show 89% expect a way to reach a human.

Trust is a factor too. Callers care who they talk to: 89% say it matters whether it is AI or a person (Salesforce), and 48% distrust information from AI service bots (Five9).

There is also a perception gap. Twilio found 90% of business leaders think customers are satisfied with conversational AI, while only 59% of consumers say they are.

Handoffs, risks and the rules for AI calls

Handoffs are where many voice AI projects fail. Twilio found only 15% of consumers reported a smooth handoff from AI to a human agent, while 78% say being able to switch matters.

Twilio's documentation describes the target: the person receives an AI-generated summary so the customer does not repeat themselves.

On regulation, the FCC decided in 2024 that AI-generated voices are artificial voices under the Telephone Consumer Protection Act. That brings consent rules into play for outbound calls.

Existing laws apply to AI as well, the FTC says.

Security matters as well. Security worries have slowed or limited AI plans for 51% of service leaders, per Salesforce. This guide is not legal advice, so check the rules for your own calls.

• Give the caller a clear way to reach a person
• Pass full context at every handoff
• Get consent before outbound AI-voice calls
• Decide what happens to recordings and personal data

How a contact center can start

Verint found 66% of surveyed leaders waited more than six months to see ROI from recent AI projects. It links that delay to trying many workflows at once instead of starting small.

A sound first step is one workflow with a clear baseline, such as after-call notes or routine scheduling calls. Measure it, then add the next one.

Cisco's survey projects over 56% of support interactions will use agentic AI by mid-2026, so planning now makes sense.

If you want a broader view of the topic first, read our guide to AI in customer service.

• Pick one workflow with a clear baseline
• Track resolution rate, handling time and satisfaction
• Add a human handoff before launch
• Scale only after the first result holds

Will AI replace call center agents?

Representative jobs are projected to fall 5 percent over 2025-2035.

It says demand is expected to be limited for occupations such as customer service representatives as AI advances.

The jobs most exposed are routine ones. Agents who handle complex, emotional or high-value contacts keep their advantage.