Two days ago, VoCoVo published the State of AI in Food and Grocery Retail 2026, a survey of food and grocery retail leaders that found every food retailer surveyed and more than 97 percent of grocery retailers consider AI critical to the future of brick-and-mortar stores. That confidence number is the highest the category has recorded. It sits alongside a second number that defines the real challenge. According to Alchemer’s 2026 Retail Report, 48.5 percent of shoppers used an AI tool to research a purchase in the past year. Only 35.4 percent trust what it tells them.
Read those two numbers together. Retailers believe AI is critical to their future. Shoppers are already using AI to make purchase decisions. And only a third of those shoppers trust the AI they are using. That is not a technology problem. It is a trust map problem. Retailers who do not know which moments in the shopping journey consumers trust to AI and which ones they still want a human for are designing their automation strategy around an assumption. Most of the time, the assumption is wrong.
The AI shopping trust gap is not about whether consumers accept AI. They do, at the research layer. The gap is about which moments in the journey still require a human, and whether the retailer has mapped those moments before designing the floor plan. Most have not.
What the Research Says About Where Consumers Trust AI and Where They Do Not
The VoCoVo In-store Intelligence report, based on 250 U.S. retail decision-makers and 500 U.S. consumers, draws a clear line. Shoppers want faster, easier experiences. They do not want those experiences to come at the expense of human connection or privacy. More than 80 percent of shoppers still see retail staff as a core part of the experience. Furthermore, poor service remains one of the fastest ways to lose a customer permanently.
Where Consumers Already Accept AI Without Hesitation
YouGov research identifies the categories where consumers are most open to AI assistance: consumer electronics, clothing and accessories, groceries and household essentials, and travel planning, each with roughly one in five consumers willing to use AI. These are high-choice, comparison-heavy categories where AI simplifies a decision the consumer already finds tedious. Additionally, Retail Dive reported on August 13 that shoppers are increasingly trusting AI to buy items on their behalf for routine and replenishment purchases. The pattern is consistent: low-consideration, high-frequency, familiar categories are where AI trust is highest.
Where They Still Want a Human in the Room
The same research draws equally clear boundaries. Consumers are least open to AI for pets, cars, and financial decisions. Sogolytics found that 47 percent of consumers will abandon a brand that misuses their data, and only 19 percent view AI as improving the customer experience. By contrast, 22 percent say AI actively harms it. The VoCoVo data confirms the underlying pattern: consumers do not want fewer staff. Both retailers and consumers in the survey see AI as augmentation, not replacement. The human is not optional. The human is the trust signal.
Why Most Retailers Are Automating the Wrong Touchpoints
The AI shopping trust gap identified by VoCoVo, Alchemer, and Sogolytics points to the same structural error. Retailers are automating based on operational efficiency. Consumers make trust decisions based on emotional readiness. Those two maps do not align by default. They have to be designed to align.
The Research-to-Purchase Gap
Consumers trust AI for research. Forty-eight percent are already using it. However, only 35 percent trust the recommendation enough to act on it without human confirmation. That gap between research acceptance and purchase trust is where most retail AI implementations stall. The retailer builds an AI recommendation engine. The consumer uses it to narrow options. Then the consumer walks to the associate to confirm the final decision. The AI did useful work. The human closed the sale. A retailer who removes the human from that moment to reduce labor cost removes the trust signal that converts the AI recommendation into a transaction.
The Service Recovery Moment
Service recovery is the moment a retailer most needs trust. A wrong order, a damaged product, a billing error, a return that does not process correctly. These are the moments when the consumer’s relationship with the brand is at stake. Sogolytics found that 33 percent of consumers are likely to switch to a competitor after just one negative experience. Automating service recovery is therefore the highest-risk automation decision a retailer can make. A chatbot handling a frustrated customer who received the wrong product is not efficient. It is a brand risk with a 33 percent customer attrition rate attached to every failure. As I described in the context of the eTail Boston AI adoption analysis, the retailers who get AI right are the ones who deploy it where it reduces friction for the customer and redeploy human attention to the moments that require it. Service recovery always requires it.
How to Build the Trust Map Before Designing the Floor Plan
The VoCoVo conclusion is precise: success depends on balance. AI that accelerates operations, colleagues who provide reassurance and connection, and clear communication that builds trust. That is not a vision statement. It is a floor plan design brief. In deployments I have worked on across the United States and Latin America, the retailers who achieve that balance do not start with the technology decision. They start with the trust map.
The trust map answers three questions for each touchpoint in the customer journey. First, is this a routine or a considered moment? Routine moments, replenishment, price checking, standard checkout, are where AI earns trust fastest. Considered moments, specialty purchases, high-price decisions, product questions, are where human presence converts. Second, what happens when this touchpoint fails? If failure means a frustrated customer with a chatbot and no human escalation path, the touchpoint is a brand risk. Third, what does the customer expect at this specific moment in this specific store format? A grocery shopper at a self-checkout lane has different expectations than a shopper at a specialty electronics counter. The automation decision has to match the expectation.
The retailers who build this map before deployment find that the technology budget and the labor budget reinforce each other. AI handles the routine layer. Human attention concentrates on the considered layer. The result is a store that operates more efficiently and feels more personal simultaneously. That is the outcome the VoCoVo data points toward, and it is the outcome most retailers miss because they sequence the technology decision before the trust map decision.
What This Means for LatAm Retailers
The trust dynamics VoCoVo and Alchemer document in U.S. retail are present in LatAm markets with additional complexity. Consumer familiarity with AI-powered retail interactions is earlier stage across most LatAm markets than in the United States. Consequently, the trust threshold for AI-assisted purchases is lower at the baseline. Consumers who have not yet formed strong AI shopping habits are more likely to want a human at touchpoints where a U.S. consumer might already accept automation.
Moreover, the service recovery dynamic is more acute in LatAm retail environments where return and exchange processes are less standardized. A customer facing a failed automated transaction in a LatAm store often has fewer alternative resolution channels than a U.S. consumer with access to brand apps, chat support, and established return policies. That makes the human touchpoint at service recovery even more critical in LatAm deployments than the VoCoVo data already suggests for U.S. retail. LatAm retailers who automate service recovery before building the human escalation infrastructure will face the same 33 percent attrition risk the Sogolytics data documents, against a consumer base with fewer alternatives and longer brand memories.
The Honest Question About Your Own Floor Plan
The Map That Changes Everything
VoCoVo CEO Beth Worrall put the design principle clearly: technology must be deployed with a clear human purpose if it is to create sustainable impact and value. That is not a call for less AI. It is a call for AI in the right place. The data from VoCoVo, Alchemer, Sogolytics, and Retail Dive all point to the same finding. Consumers are not resisting AI. They are telling retailers exactly where they trust it and where they do not. The retailers who listen are building a trust map. The ones who do not are building an automation program.
Do you know which moments in your customer’s journey consumers trust to AI and which ones still require a human? If that map does not exist in your organization before the next technology purchase order, you are designing your floor plan around your assumption about what customers want. The research says that assumption is wrong in at least 65 percent of cases, because that is the share of shoppers who use AI to research but do not yet trust it enough to act on it alone.
The AI shopping trust gap is not closing on its own. It closes when retailers deploy AI where consumers already trust it, keep humans where consumers still need them, and communicate clearly enough about both that the customer always knows which experience they are in. The retailers who map that distinction before designing the floor plan will build stores that feel more personal as they become more automated. Every other retailer will wonder why the AI investment did not produce the customer experience the vendor promised.
If you are mapping the human and AI touchpoints in your store experience or evaluating where automation is reducing trust rather than building it, connect with me here or reach me on LinkedIn. I am happy to walk through the deployment framework we use across the U.S. and Latin America.
Adriana Rivas is a retail technology executive and AI strategist, and the founder of a U.S.-based hardware company specializing in self-service kiosks, POS systems, electronic shelf labels, and digital signage deployed across the United States and Latin America. She is the award-winning author of How to Implement Self-Service Without Failing (Amazon #1 Hot New Release, Silver Nonfiction Book Award 2025) and recipient of the Gold Stevie® Award, Thought Leader of the Year 2026. She is also recognized by Thinkers360 as the #7 Global Thought Leader in Retail and a Certified Master Expert in Retail.