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Alchemer’s 2026
AI & Customer Expectations Report
What 2,000 consumers say about AI's benefits, drawbacks, and role in the customer experience.
Introduction
Ask consumers how AI has negatively impacted their experience with a company, and the top answer isn’t privacy or inaccurate information. It’s that they can’t reach a real person anymore. More than four in 10 customers name that as their single biggest problem with companies that use AI, and 43% say they would pay more for a product or service that guarantees access to human support.
What customers want hasn’t changed. They still want a person available when they need one. What has changed is how fast they expect everything else to move: 59% say that knowing a company uses AI makes them expect faster responses and issue resolutions.
Customers have a clear picture of where AI belongs in their experience with a company and where it doesn’t. Let AI handle the analysis, feedback routing, and always-on responses, and keep a person reachable when one is needed. This report covers where AI is falling short today, and what customers expect from AI and CX going forward.
Where AI Is Falling Short in the Customer Experience
According to Alchemer’s 2026 AI & Customer Expectations Study, 89% of consumers say AI has hurt their experience with a company in some way. Ask the reverse question — has AI made anything better? — and 27% say no.
Those two numbers describe different failures. The first is harm: AI did something that made the experience worse. The second is absence: AI showed up and nothing changed. Plenty of customers report both.
The complaints themselves read like familiar CX failures rather than objections to AI itself. Trouble reaching someone. Misunderstood questions. Impersonal replies. Having to repeat information.
When companies use AI, which of the following, if any, has negatively affected your customer experience? (Select all that apply)
| Negative Effect | % of Consumers |
|---|---|
| Difficulty reaching a person when I need one | 44.0% |
| Responses that don't understand my question or need | 37.3% |
| Responses that feel impersonal | 31.7% |
| Having to repeat information | 29.7% |
| Incorrect or inaccurate information | 26.0% |
| Receiving irrelevant recommendations or responses | 19.1% |
| Taking longer to resolve an issue | 18.6% |
| Concerns about how my personal information is being used | 13.2% |
| Not knowing when I am interacting with AI | 12.4% |
| I have not experienced any negative effects | 11.1% |
| Not sure | 3.3% |
| Something else | 1.3% |
1. 44% of Customers Say AI Made It Harder to Reach a Person
Difficulty reaching a person is the top complaint in the study, named by 44% of consumers. This ranks above accuracy, relevance, and privacy. Many automated systems are built to contain interactions and reduce the number of issues that reach a human agent. When containment is the main measure of success, escalation looks like failure, even when speaking with a person is exactly what the customer needs.
Customers put a price on the alternative. Forty-three percent say they would pay more for a product or service that guarantees access to human customer support. Willingness climbs sharply with AI exposure.
2. 37% of Customers Say AI Answers Miss the Question They Asked
More than one-third of consumers, 37%, have received an AI response that didn’t correctly understand their question or need. Another 26% have received inaccurate information, and 19% reported irrelevant recommendations or responses. An inaccurate answer gets a fact wrong. A misunderstood question produces a technically correct answer to something the customer never asked.
3. 32% of Customers Say AI Made the Experience Feel Impersonal
Nearly a third of consumers (32%) say AI responses have made their experience feel impersonal. They want evidence that someone understood the problem and did something about it.
A polished automated acknowledgment is no substitute for follow-through. Customers feel heard when the company routes their feedback to someone who can act, makes a change when it’s warranted, and closes the loop.
4. 30% of Customers Are Repeating Information They Already Provided
Having to repeat information is a negative effect for 30% of consumers. A survey response may live in one system, a review in another, and a support case in a third. When those records aren’t connected, every interaction starts over. It’s most frustrating when a customer moves from AI to a human agent and has to repeat everything they just explained.
Repetition also undermines the reason many companies adopt AI in the first place. If automation adds a step without shortening the path to resolution, the customer loses both speed and personal service. That’s already happening for the 19% who say AI has made issue resolution take longer.
The Customers Who Use AI Most Are the Most Skeptical of It
One pattern runs through the whole study: familiarity with AI doesn’t produce comfort with it. The consumers who use AI everyday report more problems with it, worry more about what it gets wrong, and are the most willing to pay to keep human support within reach.
Start with what they’ll pay. Daily AI users are more than 2.5 times as likely as infrequent-users to say they would pay extra for guaranteed human support, at 27% compared with 10%. They’re also the least likely to rule it out: 13% of daily users say they wouldn’t pay, against 31% of infrequent users. And among the consumers willing to pay a steep premium, 20% or more, nearly half are daily AI users.
The same split shows up in how the experience lands. Forty percent of daily AI users say AI has made their experience feel impersonal, compared with 22% of people who don’t use AI as often. Additionally, thirty percent of daily users worry about AI reaching inaccurate conclusions, compared with 20% of people less familiar with the tools.
Where Customers Want AI to Improve the Customer Experience
Customers are specific about the work they want AI to do. Speed leads the list in two ways: how quickly a company responds when feedback is provided, and how quickly the problem is resolved.
After speed, they want AI to understand what they need, make information easier to find, and remember what they’ve already shared.
When companies use AI, which of the following, if any, would you most like to improve about your customer experience? (Select all that apply)
| Desired Improvement | % of Consumers |
|---|---|
| Faster resolution of issues | 37.9% |
| Faster responses | 33.5% |
| Better understanding of your needs | 28.8% |
| Easier access to information | 24.3% |
| Less need to repeat information you've already provided | 23.7% |
| More relevant or personalized experiences | 23.7% |
| Easier access to a person when needed | 17.9% |
| I don't want AI involved in my customer experience | 16.5% |
| Faster action on feedback you provide | 14.0% |
| More consistent experiences across different interactions | 11.4% |
| None of these | 2.2% |
| Something else | 1.1% |
1. 38% of Customers Want AI to Drive Faster Issue Resolution
Faster issue resolution ranks first, selected by 38% of consumers. Another 34% want faster responses. The distinction between the two matters: a quick reply can acknowledge a question without solving it, while resolution means the customer’s problem is gone.
First-response time shows how quickly an automated interaction moved. It doesn’t show whether the customer got the help they needed. A chatbot session can look successful because it ended without an escalation, but if the customer calls two days later about the same unresolved issue, the experience was neither efficient nor complete.
2. 34% of Customers Want Faster Responses, and AI Has Already Reset What Fast Means
According to Alchemer’s research, 59% of consumers say that knowing a company uses AI to analyze feedback makes them expect a faster response.
The expectation isn’t limited to interactions AI handles. Forty-five percent say advances in AI have raised what they expect of companies overall. Nearly 30% expect a company to acknowledge their feedback within 24 hours, and 16% expect acknowledgment immediately.
That expectation follows customers to every channel where they share feedback: a public review that sits unanswered, a survey response that disappears into a reporting tool, a support ticket with no follow-up. Automated acknowledgment can meet the need for immediacy, but it has to be clear about what has and hasn’t happened. A message that confirms receipt and sets expectations reduces uncertainty. A generic response that implies resolution when nothing has been done costs trust.
3. 29% of Customers Want AI to Help Brands Understand Their Needs
Better understanding of customer needs ranks third at 29%, and more relevant or personalized experiences sits close behind at 24%. The two often get treated as one request. They aren’t. Understanding means recognizing the customer’s intent and answering the question in front of you. Personalization uses previous data or behavior to tailor the experience. Understanding comes first, because a personalized answer that misses the customer’s actual need is still a poor answer.
The same split appears in what customers expect after they share feedback: 22% expect the company to understand their issue or suggestion, and 21% expect a personal response when the situation calls for one.
4. 24% of Customers Want AI to Make Information Easier to Get To
Nearly one in four consumers in the study, 24%, want AI to make information easier to access. To do that well, companies need to know where customers are already sharing questions and feedback. Surveys remain the most common feedback channel at 60%, followed by online reviews at 49%. Live chat accounts for 23%, and website feedback forms 20%.
That mix creates a challenge for CX teams. Chat and website forms are easy to connect to internal workflows because the company owns them. Reviews are public and spread across outside platforms, and surveys are often managed separately from service and operational systems.
When those sources stay disconnected, teams see only part of the customer story. AI can help customers find answers, and it can also help companies find the issues hidden across those channels. Bringing survey responses, reviews, support conversations, and other signals together makes it easier to spot recurring problems and respond consistently.
A Customer-Centered Approach to AI
Alchemer’s 2026 AI & Customer Expectations Study points to five practical priorities for CX leaders.
1. Keep human support within reach
Customers shouldn’t have to outsmart an automated system to reach a person. With 44% naming human access as AI’s biggest cost and 43% willing to pay more to guarantee it, escalation needs to be easy to find and use, especially for complex, sensitive, repeated, or high-risk issues. The way the program is measured matters too. If containment is the only goal, teams have an incentive to limit escalation even when a human conversation would produce a better outcome. Balance efficiency metrics with resolution, repeat-contact rate, customer effort, and satisfaction.
2. Measure the full issue, not one interaction
Track the customer’s journey across sessions and channels. A chatbot conversation that ends quickly but leads to a phone call about the same issue is not a completed resolution, and 19% of consumers already say AI has made resolution take longer. Connecting those interactions shows whether AI is reducing effort or moving it somewhere else.
3. Preserve context at every handoff
Customers shouldn’t have to repeat information the company already has, yet 30% say they’ve had to. Connect survey feedback, reviews, service history, and relevant customer data so each interaction begins with context. Pay particular attention to the handoff from AI to a person. The customer’s original question, previous answers, and steps already taken should move with them.
4. Turn feedback into visible action
Taking appropriate action is what customers want most after they give feedback, at 48%, and 36% want to hear when that action has been taken. Use AI to analyze open-text feedback, surface recurring issues, and route signals to the team that owns the next step. Then tell customers what happened. Customers don’t experience an internal alert, a dashboard update, or a newly created ticket. They experience the change, or the silence that follows their feedback.
5. Build trust through transparency
Thirteen percent of consumers cite concerns about how their personal information is used, and 12% point to not knowing when they’re interacting with AI. Explain when AI is being used and how customer data supports the experience. Publish clear data practices, identify relevant security standards, and give customers choices where possible. Trust isn’t a one-time disclosure. It’s the result of using customer information carefully, producing reliable outcomes, and making it easy to reach a person when needed.
Introducing Alchemer Iris
Customers have defined the role they want AI to play. They want faster resolution, quicker responses, easier access to information, and less repetition. They also want a person available when the situation requires one. That doesn’t force a choice between automation and human support. It calls for a better division of labor: AI handles the volume work of analyzing feedback, spotting patterns, and routing issues, while people stay at the center of moments that require empathy, judgment, or accountability.
Those tasks are what Alchemer Iris is built on: the AI-native, human-first platform for customer feedback and intelligence that asks the next question, brings answers into focus, and turns signals into action.
- Every signal in one place. Surveys, in-app feedback, reviews, social, and listings come together in a single view, so context follows the customer instead of stranding them in whichever system they started in.
- The right AI for each job. Iris uses techniques purpose-built for feedback data, not one model for everything — detecting themes and intent in real customer language, including the mixed feedback buried inside a single response.
- Insight that triggers action. Feedback connects to the workflows your team already runs. Alerts fire, issues route to the owner who can fix them, and teams close the loop while the problem is still fresh.
- You decide what AI touches. Controls, approvals, and guardrails let you automate where speed helps and keep a person where judgment matters. Your data never trains a model outside your walls.
And the one place you’ll never find AI? Alchemer’s human support. 81% of new customers rate Alchemer’s support better than what they had before.
According to Alchemer’s 2026 AI & Customer Expectations Study:
- 59% of consumers expect a faster response once they know a company uses AI to analyze feedback, and 30% expect a much faster one. Announcing AI creates a service obligation
- 38% of consumers want AI to deliver faster issue resolution, the top-ranked improvement, and a different measure than the 34% who want faster responses
- 37% of consumers have received an AI response that missed the question they actually asked
- 32% of consumers say AI has made their experience feel impersonal, rising to 40% of daily AI users vs. 22% of never-users
- 30% of daily AI users worry about AI reaching inaccurate conclusions, vs. 20% of consumers who’ve never used AI. Familiarity breeds scrutiny, not comfort
- 30% of consumers have had to repeat information they already provided, and 19% say AI made resolution take longer
- 27% of consumers say AI has delivered no tangible benefit to their experience at all
- 17% of consumers don’t want AI involved in their customer experience at all
- Just 11% of consumers report no negative effects from company AI, meaning 89% have experienced at least one
- 20% of consumers quietly buy less after a poor feedback experience, while only 8% leave a public review. Most of the damage never reaches your review data
What 2,000 consumers say about AI's benefits, drawbacks, and role in the customer experience.