AI Agents Consumer Trust: Closing the Agentic Commerce Gap

Brands are moving faster on autonomous AI than the people they serve are willing to follow, and new data proves it. AI agents consumer trust has become the defining friction point of the agentic era, with enterprise ambition sprinting ahead of everyday shopper comfort. A fresh Acxiom study released this week found that the vast majority of brands expect consumers to hand purchasing decisions over to AI, while only about half of consumers actually feel that way.

That gap landed in the same week Zillow plugged its listings directly into Anthropic's Claude, and B2B platform Demandbase launched a suite of agents built specifically to help brands get noticed by AI assistants. Three separate signals, one unmistakable pattern: autonomous AI is no longer a future state. It is being built into checkout flows, home searches, and B2B buying journeys right now, often faster than consumer sentiment can catch up.

Matt Britton has spent his career tracking exactly this kind of collision between technology adoption curves and human behavior. As founder of Suzy and author of Generation AI, Britton built his reputation studying how real consumers, not just boardroom projections, respond to disruptive technology. He now brings that lens to Fortune 500 stages as one of the most sought-after AI keynote speakers addressing the agentic commerce shift.

Britton's core argument is simple but uncomfortable for executives racing to deploy agentic tools: building the technology is the easy part. Earning permission to let it act on a customer's behalf is the hard part, and most brands have not done the work. This piece breaks down what the new data actually says, how companies like Zillow and Demandbase are responding in real time, and what business leaders need to do before their own AI agents outpace customer trust.

What Is the AI Agents Consumer Trust Gap?

The AI agents consumer trust gap describes the measurable distance between how much autonomy brands expect consumers to grant AI systems and how much autonomy consumers are actually willing to give. Acxiom's newly released CX Trends Report puts a hard number on it. Acxiom research finds 86% of brands believe consumers will accept AI making choices for them, while only half of consumers agree. The report is based on 4,000 consumer interviews and 700 brand interviews across the U.S. and UK, examining how artificial intelligence is evolving from an advisory tool into an autonomous decision-maker in customer experience.

This is not a one-year anomaly. Acxiom's prior annual study found agreement between brands and consumers on the speed with which AI is reshaping CX, with 93% of brands and 70% of consumers believing it's moving faster than they're ready. That same research uncovered a sharper nuance worth sitting with: while 83% of consumers are open to brands using AI to influence their decisions, a firm 65% state that if AI decides for them, it stops being their experience. Consumers like AI as a co-pilot. They resist it as the sole driver.

Acxiom CEO Jarrod Martin framed the tension well, noting that "the paradox between AI's potential and the customer's desire for control isn't a roadblock; it's the next great challenge for brands to solve." Matt Britton echoes that framing in his keynote work, arguing that brands conflating AI capability with AI permission are setting themselves up for a backlash, not a breakthrough. The businesses expecting the fastest payoff, the 79% of brands that expect AI-curated experiences to transform their sector in the next 12 months, are precisely the ones most exposed if they skip the trust-building step.

Agentic Commerce Arrives: Zillow's Claude Integration and the B2A2C Blueprint

While Acxiom was publishing its warning, Zillow was demonstrating one way to act on it responsibly. On October 19, 2026, Zillow Group announced the integration of its real estate platform with Claude, an AI assistant, enabling users to search homes for sale or rent directly through conversational AI. The move extends a pattern already underway, since Zillow already runs comparable experiences in ChatGPT and, for rentals, in Gemini.

What makes the Zillow launch notable is not the integration itself but the terms behind it. Zillow stated that it sends no data to Anthropic; its own MLS-approved listing display appears inside Claude with the same broker and MLS attribution as on Zillow.com, and a buyer can request a tour, reach an agent, or explore financing without leaving the conversation. Industry analysts are already calling this the business to agent to consumer (B2A2C) model, with the brand's commercial terms written in, and suggest every brand with a connector roadmap should ask its partners for the same terms.

Zillow's SVP of AI, Josh Weisberg, tied the launch directly to trust rather than novelty, noting that home searches deserve "specialized intelligence, real listings, real home values and real affordability math, built on two decades of housing data." That is the permission-first instinct Matt Britton tells real estate, finance, and retail audiences to replicate: let the agent act, but keep the brand's data, attribution, and lead ownership intact. For industries wrestling with exactly this tension, Britton's work on the AI speaker real estate track breaks down how property and lending brands can adopt agentic tools without surrendering the customer relationship.

Brands Build for AI Agents: Demandbase's AEO Push and the B2B Shift

The trust gap is not limited to consumer purchases. A parallel battle is unfolding in B2B, where brands now have to win over AI assistants before they ever reach a human buyer. On October 20, 2026, Demandbase launched an AEO Agent, a Campaign Agent, and an Audience Agent at its GO conference in New York.

The AEO Agent, short for answer engine optimization, is built to solve a very specific version of the trust problem. Drawing on more than 342 million contacts across 13 million companies, marketers can compare how major AI assistants describe and recommend their company to each individual buying group member, assess visibility across relevant questions, and identify sources informing AI-generated answers. Demandbase is not guessing at urgency here. The company cited a Gartner prediction that AI agents will intermediate 90% of B2B buying by 2028.

This matters for the same reason the Acxiom data matters: brands are optimizing for AI systems that act as gatekeepers before consumers ever enter the picture. Matt Britton frequently points audiences to this shift during his Speed of Culture conversations, where he and guests unpack how go-to-market teams are rebuilding content, data, and distribution strategy around machine readers instead of human scrollers. Executives can follow that ongoing analysis on the Speed of Culture podcast, where Britton tracks these shifts in near real time.

The Enterprise Adoption Paradox: Speed Without Scale

Underneath both stories sits a broader paradox that Matt Britton has named directly in his keynotes: enterprises are adopting agentic AI faster than they are scaling it responsibly, and faster than consumers are prepared to accept it. The numbers back him up.

• Enterprise intent is sprinting ahead. Gartner predicts 40% of enterprise applications will feature task-specific AI agents by the end of 2026, up from under 5% in 2025.
• Production reality lags far behind. PwC puts current adoption at 79%, while Capgemini finds only 2% of organizations have deployed agents at scale, with another 12% at partial scale.
• CIOs confirm the acceleration curve. Only 17% of organizations have deployed AI agents to date, yet more than 60% expect to do so within the next two years, the most aggressive adoption curve among all emerging technologies measured in the survey.

Read together, these figures describe an industry building the plane while selling tickets. Brands are telling boards and investors that autonomous AI is already transforming customer experience, while internal deployment data shows most of that transformation is still in pilot mode. Matt Britton's position, laid out at length in Generation AI, is that this mismatch between stated ambition and actual readiness is exactly what erodes consumer confidence before an agentic product ever ships.

Closing the AI Agents Consumer Trust Gap: A Permission-First Playbook

Closing the AI agents consumer trust gap requires brands to treat trust as a measurable, buildable asset rather than an assumed byproduct of good technology. Britton advises clients to start with transparency: tell consumers explicitly when an AI agent is acting, deciding, or simply advising, since consumers remain far more comfortable with AI influencing a decision than making it outright. Zillow's approach, keeping listing data, attribution, and lead routing under its own control even inside someone else's AI interface, offers a template other industries can study.

Brands also need real-time visibility into how both AI systems and actual customers perceive them, not just internal roadmap confidence. Platforms like Suzy, the consumer intelligence company Britton founded, exist precisely to close that gap by surfacing authentic consumer sentiment before it shows up as churn or backlash. Pairing that human-side data with AEO tools that monitor how AI assistants describe a brand, the same instinct behind Demandbase's new agent suite, gives leaders a fuller picture of readiness on both sides of the transaction.

Generational differences compound the challenge further. Younger consumers tend to show markedly higher comfort with autonomous AI than older cohorts, a dynamic Britton unpacks in depth for audiences through his Gen Z keynote speaker programming. Brands rolling out agentic commerce uniformly across all customer segments risk alienating the very shoppers least ready for it while under-serving the ones most eager for it.

Key Takeaways for Business Leaders

• Measure the gap between your brand's AI ambition and your customers' actual comfort level before scaling any autonomous purchasing feature.
• Disclose clearly when AI is advising versus deciding, since consumers tolerate influence far more than outright autonomy.
• Retain control of your own data and lead routing when integrating with third-party AI assistants, following the B2A2C model Zillow established with Claude.
• Monitor how AI assistants describe and recommend your brand using AEO tracking, since machine gatekeepers now shape B2B and consumer discovery alike.
• Segment your agentic rollout by generation and risk tolerance rather than deploying one-size-fits-all autonomy across your entire customer base.

Frequently Asked Questions

What is the AI agents consumer trust gap?

The AI agents consumer trust gap is the measurable difference between how much decision-making authority brands expect consumers to hand over to AI and how much consumers actually want to grant. Recent Acxiom research found 86% of brands expect this autonomy, while only about half of consumers agree, revealing a significant readiness mismatch businesses must address before scaling agentic commerce.

Why do consumers hesitate to let AI make purchasing decisions?

Consumers generally welcome AI as an advisor but resist it as a decision-maker because autonomy feels like losing control over a personal choice. Acxiom's research found that while most consumers accept AI influencing a purchase, a strong majority say the experience stops feeling like theirs once AI decides for them outright, not just suggests options.

What is agentic commerce and how does it work?

Agentic commerce refers to AI systems that independently search, evaluate, and sometimes complete purchases on a consumer's behalf, often inside a conversational assistant like Claude or ChatGPT. Zillow's recent Claude integration is a working example, letting users search listings and move toward a tour or loan while Zillow retains control of its data and leads.

How can brands close the AI readiness gap with consumers?

Brands can close the AI readiness gap by being transparent about when AI is deciding versus advising, retaining ownership of customer data within third-party AI integrations, and continuously measuring real consumer sentiment rather than relying on internal assumptions. Matt Britton advises treating trust-building as a parallel workstream to technology deployment, not an afterthought.

The agentic era will not be won by whichever brand ships the most autonomous AI agent first. It will be won by the brands that earn the right to act on a customer's behalf, one transparent, well-governed interaction at a time. Matt Britton has built his career translating exactly this kind of inflection point into clear, actionable guidance for executive teams navigating consumer behavior shifts.

As Zillow, Demandbase, and a wave of other companies race to embed agentic AI into commerce and marketing, the brands that pair technical ambition with real consumer trust data will separate themselves from those chasing headlines. Matt Britton brings this exact analysis, grounded in proprietary consumer research and real-time trend tracking, to stages for Fortune 500 companies worldwide. Organizations ready to prepare their teams for the agentic shift can learn more and book Matt Britton through Speaker HQ today.