A year ago, integrating AI into the buying journey was still debatable for consumer brands. They were rushing to deploy it and consumers were openly resistant to it, while marketing and CX leadership anxiously analyzed whether the risk was worth it.
A year later, the debate has quieted, mostly because the AI got better. It's faster, more polished, and more useful. So good, in fact, that nearly two-thirds of US consumers can't reliably tell when they've been talking to AI or a person. And the share who say their last AI interaction made things worse has dropped sharply since last year.
The brands that deployed AI well in the last year have been rewarded by consumers who are grateful for rapid, reliable service. In many cases, it's so good that consumers just didn't care whether it was AI helping them or not. But when AI interactions go wrong, keep in mind that consumers are quick to blame the brand that chose to deploy it, not the vendor who made it for you. By nearly three to one.
That's the headline of the 2026 B2C Buyer Experience Study, and it changes the calculus of AI investment for marketing and CX leaders. AI is no longer a futuristic add-on or a risky experiment. It's table stakes. The question is no longer whether to use AI in the customer journey. It's whether your AI is good enough to protect your brand and hand off to a human when it can't.
Read on for what consumers told us, what's changed since 2025, and where the data points your CX investments next.
The negative sentiment that defined the 2025 conversation about brand AI has softened across nearly every measure, suggesting the technology is improving. Fewer consumers feel less valued, and feel forced to use a brand's AI less often. More telling is the 11-point drop in those who said AI made their buying experience worse.
And yet, the share who say AI made their experience meaningfully better has only ticked up modestly. The bulk of the movement is from "worse" to "neutral." AI is no longer making a bad impression — it's making no impression at all. For consumer-facing technology like this, going unnoticed is often the goal.
For brands, the implication is that the bar for AI deployment has shifted. A year ago, the question was how to deploy AI without alienating customers. Now, the question is how to deploy it well enough that customers don't notice, and how to make sure that when they do, they're glad it was available.
“If it helps solve my problem quicker then it is fine.”
— Boomer, healthcare / telecom purchase
One of the most striking findings in the 2026 data is also the simplest. When we asked US consumers whether they had ever realized, after the fact, that an interaction they thought was with a human was actually with AI, only 37% said yes. The other 63% either said they have never had that realization or weren't sure.
This is an indication that AI technology has crossed a quality threshold. A year ago, brand AI was identifiable by its stiffness, scripts, and a general refusal to deviate from preset paths. Today, voice and text AI is good enough that many consumers can't reliably distinguish it from a human agent. That's a win for the technology and a win for the brands that deployed it carefully.
“Because artificial intelligence is so lifelike it’s really no different than talking with human beings.”
— Millennial, multiple categories
We asked consumers when an AI interaction with a brand goes badly, who do you primarily blame? The result is a wake-up call for any CMO or CX leader who treats AI deployment as a vendor decision.
While it's awful nice of the nearly 20% who don't blame anyone, those who blame the brand for AI missteps outpaces blame the AI by nearly 3 to 1. Add the consumers who hold the brand at least partially accountable, and roughly two-thirds of US consumers will tie a bad AI experience back to the company that chose to deploy it. The vendor takes none of the heat. The customer's relationship is with the brand, and so is their disappointment when AI lets them down.
“The company does not care enough to hire or get humans to properly handle customer service.”
— Gen X, travel purchase
Consumers have definitely made up their minds about whether AI should identify itself in customer interactions. Over 80% say that it matters that a brand's AI clearly identifies itself. Consumers will not wait for regulators to force the issue. They already expect disclosure, so for brands, this is a low-cost, high-trust tactic to deploy now.
“I feel they should let you know before throwing you to AI. It feels like a lie.”
— Millennial, automotive / healthcare purchase
A year ago, 60% of US consumers said they felt forced to interact with a brand's AI most or all of the time. This year, that figure has dropped only slightly.
The risk for brands is complacency. Consumers are fickle, and while they are more accepting of AI assistance overall, over 40% still feel that brands that use AI to assist them value them less. This hasn't changed much since last year, and it's a reminder that improvement must be continuous to keep your customers satisfied.
“I like AI, but I don’t want to be forced to resort to AI instead of a real person. I also don’t want to opt for AI, because while it is a great tool, it isn’t as great as talking to a real person.”
— Gen X, automotive / healthcare purchase
We asked consumers when they actually prefer AI to a human, and the answers are remarkably consistent with last year — simplicity and speed win.
The "avoiding waiting on hold" finding is the one that should move investment decisions. More than one in three US consumers will choose AI specifically to avoid a hold queue, meaning brands without a competent AI frontline are losing good leads at the moment they're most likely to convert.
These are also the moments in a high-stakes buying journey that determine whether a sale happens. AI handles the easy turns. Humans still close the deal.
“I like AI for quick answers, but for complex stuff or big decisions, I want a human who can actually understand my situation. Best of both worlds.”
— Millennial, multiple categories
If there's a single piece of data in this report that should change a marketing budget, it's the gap between what consumers expect and what they actually get in terms of response speed after filling out a lead form.
That's a 20-percentage-point gap between expectation and delivery, and a near-universal willingness to walk if a faster option appears.
What do consumers do when the response is too slow? 46% try to contact the brand again, but 27% move to a competitor, and another 3% give up on the purchase entirely. Only 24% wait it out. The cost of a slow response isn't a delayed conversion. It's a lost one.
“I start wondering if they really care about getting my business and usually look for faster more responsive options.”
— Gen Z, travel purchase
For all the talk of digital-first buying journeys, US consumers still pick up the phone when they need help with a high-stakes purchase. 41% prefer calling when they have a problem and need help — more than any other channel. The phone has steadily been the consumer's preferred help channel over the last three years, rising from 32% in 2022 to 44% in 2025 and holding at 41% in 2026.
The age pattern strengthens the story. 52% of US Boomers prefer calling for help, with another 33% preferring in-person assistance — together accounting for 85% of Boomer help preference. Gen X tracks closely behind at 44% calling and 27% in-person. Gen Z and Millennials are meaningfully more open to email, online, and AI assistants when they need help, but still default to phone above any other channel. The brand that wins the older consumer journey has to invest in phone (and the in-person handoff) at full strength. The brand that wins the younger consumer journey has to make every digital help channel work too.
“I would rather speak with a human if possible, feel I’d get clearer response in that moment.”
— Gen X, home services / travel purchase
When US consumers call a business during a high-stakes purchase, they're most often seeking more information. These are expensive, even life-altering purchases, and consumers want to be confident they're making the right decision.
Disturbingly, 26% called because the information they needed wasn't available online, a stat that has barely moved in three years despite continued investment in digital experiences.
Closing this online information gap is one of the highest-leverage CX investments a brand can make. Every call driven by a missing fact on a website is a call that didn't need to happen.
“Trust issues. Am I getting all my questions answered? Sometimes feels like conversation going in circles. I can hear in a human if I am getting all the information I need and if they sound trusting.”
— Gen X, home services / financial services / travel purchase
We asked consumers whether they had used a generative AI tool, like ChatGPT, Gemini, or Claude, to help research a high-stakes purchase. The result is one of the biggest year-over-year shifts in the dataset.
The gap between brand AI and generative AI is closing fast on the consumer side. A year ago, generative AI was something younger consumers experimented with. This year, it's a default research step for most adults.
This is a marketing problem as much as a sales one. Brands need to know what generative AI says about them, because their prospects already do.
The biggest generational shift in this year's data isn't among the digital natives. It's among the older holdouts.
Gen X moved nearly as much. 53% of US Gen X consumers used gen AI for research, a substantial gain over 2025. Millennials and Gen Z continue to lead in absolute terms at 71% and 69% respectively, but they were already there a year ago. The story of 2026 is the rest of the audience catching up.
Boomers haven't softened on every front. 85% of US Boomers still prefer a human representative when both options are equally available, the same direction as 2025 but with the same intensity. 92% say human connection is important during a high-stakes purchase.
The picture that emerges is of an older audience that is now using generative AI as a research tool, while still preferring human-led conversations when they're ready to make the decision. The implication for brands targeting older consumers: AI matters at the discovery stage, humans matter at the close.
The human-preference gradient extends across every generation, though. The buying journey may be increasingly AI-mediated upstream, but the moment of decision is still a moment of human contact for the audiences brands depend on most.
“I’m thinking it saves time and makes the process easier, especially when I just need quick answers or updates without calling customer support.”
— Boomer, telecom purchase
For all the AI advances, US consumers haven't changed their mind about what they want at the moment of a high-stakes purchase decision. Nearly 60% prefer human help to AI when both are equally available, and an overwhelming 96% said that a human connection during a high-stakes purchase is important.
These numbers are essentially flat versus 2025, and the floor hasn't moved. Across every generation, every industry, and every channel preference cut, US consumers continue to anchor the moments that matter on human contact. The 2026 data simply adds a layer of nuance: AI is welcome in the journey, especially upstream, but the human stays in the loop when the customer is ready to commit.
“Humans would help better with complex situations and be more flexible and more empathetic with solutions.”
— Gen X, automotive / telecom purchase
These two data points look contradictory at first, but tell a connected story on a second look.
Consumers will not wait. They expect to be heard, and if they're not, they'll abandon the call but not necessarily abandon the brand.
The stop-doing-business number is the more nuanced finding. Consumers became substantially more forgiving year-over-year, a 26-point drop in the share saying they'd stop after one bad experience. They're willing to put up with one bad experience. They're not willing to put up with the journey to that experience. The brand that picks up the phone (or offers satisfactory AI assistance) quickly earns the right to make a mistake. The brand that leaves the customer on hold for an hour doesn't even get the chance.
“It also makes me feel like my purchase and time are not important, which in the long run defers me from returning as a customer.”
— Millennial, telecom / travel purchase
This year, for the first time, we asked US consumers whether they had spoken to an AI voice agent on the phone during a recent purchase journey. The result confirms what brand-side data has been hinting at for months.
That's a majority who have either definitely or possibly spoken to an AI voice agent in the last year. The market has moved from novelty to ubiquity faster than any prior CX automation wave we've measured. Among consumers who interacted with an AI voice agent, the modal answer when asked how the interaction compared to a human is "about the same," which is exactly where a new technology should be after 12 months of deployment.
“I was getting more accurate responses and being able to get what I needed without attitude and being put on hold.”
— Gen X, telecom purchase
The 2026 data describes an inflection point. The brands that win the next chapter of the buying journey are the ones that treat AI as a brand-equity decision, deploy it well enough that consumers don't notice in good moments and trust the disclosure in bad ones, and connect every AI touchpoint to a human moment when the buyer is ready to commit.
The phone is still where the decisions get made. The data is still where the optimization happens. The brand that connects the two, and that does it with AI that respects the consumer, wins.
Learn more at invoca.com →For this report, Invoca surveyed 1,356 consumers in the US and UK who researched and made a high-stakes purchase in the last 12 months across seven industries: automotive, healthcare, home services, insurance, financial services, telecommunications, and travel. Only US data is used in this version of the report, representing 693 respondents. A high-stakes purchase is one where consumers take time to weigh options, research, and put more thought into the decision because of cost or complexity, generally above $500, or above $1,000 for travel. Results may not total 100% due to rounding and multi-select question formats. The field survey was performed via the Trycycle Gather conversational survey platform between May 8 and May 22, 2026.
Results may not total 100% due to rounding and multi-select question formats. Multi-select questions are clearly flagged on each chart. Year-over-year comparisons reflect minor differences in question wording where noted in the body of the report. The "industry" cut is based on the high-stakes purchase the respondent made in the last 12 months and is multi-select, so a single respondent could appear in more than one industry if they purchased across categories. Generational definitions follow the Pew Research Center cutoffs. Powered by Gather (gatherhq.com).