Consumer Trust Lags Behind AI Adoption in Retail, New Research Shows
Nearly three out of four Americans know about AI shopping agents, but only 39% trust them to make everyday purchases. That gap between awareness and trust is the real problem brands need to solve.
A new report from The Harris Poll, presented by Quad, surveyed 2,180 U.S. adults in February 2026 to understand how consumers engage with AI during shopping. The findings reveal a disconnect: awareness doesn't equal confidence. Brands are effective at getting people to consider AI-powered shopping tools, but something else is needed to convert that consideration into actual purchases.
The Missing Ingredient: Physical and Digital Consistency
Brands need to blend digital and physical experiences to build trust. The research found that 81% of Americans say a strong in-store experience makes them more confident trying new products from that brand online.
Consumers also said it's easier for brands to misrepresent product quality online than in physical stores. This means brands can't treat their online, at-home, and in-store experiences as separate channels. They need to be consistent across all three.
Rethinking AI as a Matchmaking Tool
AI works best when it connects the right product attributes to the right customer. Consider buying a jacket: a rock climber needs performance features and fit under a harness, while someone buying for casual dog walks has different priorities. The product is the same, but the needs are different.
AI can capture those distinctions if brands invest in stronger product data first. That means enriching product metadata for language models, building genuine customer reviews, and collecting user-generated content. The groundwork matters more than the AI itself.
Physical Retail Isn't Disappearing-It's Evolving
The framing of "AI versus physical retail" is wrong. The data shows it's "AI plus physical retail." When done right, they complement each other.
Consumers view AI as a tool to reduce friction: 60% of Americans cite spotting pricing inconsistencies, staying on budget, and narrowing choices faster as reasons to use AI shopping agents. But they still value stores for what they offer that digital can't-social interaction, sensory experience, and fewer decision fatigue moments.
AI is reshaping retail's role, not replacing it. Consumers want AI to build confidence before purchase and stores to provide human, sensory experiences.
Transparency on Sponsored Results Is Non-Negotiable
The research was unambiguous here: 75% of Americans would trust AI agents less if brands paid to influence results. That same 75% would trust the brands themselves less.
When influence exists in an AI system, it must be transparent to consumers. Without transparency, brands don't just lose a transaction-they risk losing the relationship entirely.
What This Means for Product Development
For teams building AI for Product Development, the priority is precision at the point of sale. Brands that connect AI-driven targeting upstream with strong physical shelf experiences win.
Product developers should focus on enriching data quality and ensuring that AI recommendations reflect genuine customer needs, not just commercial incentives. The technical capability matters, but consumer trust determines success.
AI for Marketing teams face a similar challenge: speed and scale matter, but only when paired with precision. The brands winning now are those connecting AI intelligence across the entire marketing lifecycle while maintaining consistent, trustworthy experiences wherever customers encounter them.
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