AI is changing customer service quickly, but customers are giving companies useful guidance about what they actually want from it. The short version: they will use automated support when it consistently solves the problem, and they will give up on it fast when it creates more work.
Recent research points to an interesting pattern. People are still open to automation when it makes getting help easier. What they have less patience for is an automated experience that adds effort.
An April 2026 study of 6,000 consumers across the U.S., U.K. and Canada found that 85% preferred speaking with a real person when contacting a business, up from 83% in October 2025. At the same time, 59% said they felt frustrated with AI agents, up from 54%.
That doesn't mean there is no appetite for automation.
It means customers are becoming more specific about where they want it.
A simple question with a simple answer is a natural place for AI. A complicated billing issue, a sensitive problem or a situation that requires judgment can call for something different.
The opportunity for CX leaders is to design around those differences.
Parloa's 2026 Consumer Patience Index offers another useful signal.
In its survey of 1,001 U.S. consumers, "talking to a bot that doesn't understand me" ranked as the most frustrating support experience. More than half of respondents, 55.5%, said they would disengage from automated support within three minutes if it wasn't resolving their issue.
At the same time, the research found that 84.9% would continue using automation if it reliably solved their issue.
Customers are simply asking for service that works.
If AI can understand the request, provide a useful answer and move the customer toward resolution, there is a strong reason to use it.
When the situation requires judgment, empathy or context that the system doesn't have, the experience needs a clear path to human help.
This creates a bigger opportunity than simply automating existing service processes.
AI gives companies the ability to rethink how service works from the ground up.
Instead of asking, "Where can we put a chatbot?" teams can ask:
Where does the customer need speed?
Where would better information make the experience easier?
Where can AI help an employee make a better decision?
Where does a customer still benefit from human judgment?
What should happen when the AI doesn't know the answer?
Those questions lead to very different designs.
AI might handle the first step of a request, gather the relevant information and prepare everything an employee needs to resolve a more complicated issue. It might help an agent understand a customer's history before the conversation begins. It might identify patterns across thousands of interactions that would be almost impossible to spot manually.
The technology becomes part of a larger service system.
One of the biggest opportunities is connecting AI and human service more thoughtfully.
Imagine a customer starts with an AI assistant and gets help with a routine question. Later, the issue becomes more complicated and needs a person.
The customer shouldn't have to start over.
The employee should have the context. The system should know what has already been discussed. The customer should be able to move between AI and human support without feeling like they have entered an entirely different service experience.
That is where AI can do something especially valuable: make the human interaction better.
The same Parloa research found that 86.7% of consumers consider feeling understood important to their support experience, even when the interaction is automated.
That gives CX teams a useful design principle.
Use AI to help customers feel understood faster.
The most interesting future for AI in customer service may have less to do with replacing interactions and more to do with improving them.
AI can help customers get answers faster.
It can help employees enter conversations with more context.
It can make information easier to find.
It can identify recurring problems and patterns in customer behavior.
It can help companies see where customers are struggling before those issues become larger service problems.
And it can create more capacity for people to spend their time where judgment and human connection add the most value.
That is a much bigger opportunity than simply reducing the number of calls handled by people.
The companies that get the most from AI in customer service will have an opportunity to start with a simple question:
What would make this experience easier for the customer?
From there, AI becomes one of the tools available to create that experience.
The research suggests customers are willing to use automation when it works. They also continue to value people when they need them.
That gives CX leaders a clear direction: design the experience first, then determine where AI, people and technology can each contribute.
Andrew Reise, a customer experience consulting firm, helps organizations identify where AI can create value across the customer experience, define the right role for people and technology, and build a practical path from opportunity to implementation. You can see how we approach it on our AI strategy for CX, EX, and the contact center page.
If you are deciding where AI should show up in your customer experience, we can help you identify where to start.