The future of retail may not depend on whether consumers use artificial intelligence, but on how far they are willing to let it act on their behalf.
The data suggests AI users drive larger baskets and higher-value transactions. A Bayes Business School study of more than 12,000 supermarket trips found that shoppers using AI-assisted smart carts spent up to one-third more than those who did not.
Likewise, Adobe’s transaction data points in the same direction. During the 2025 holiday season, AI-referred traffic converted 31% more frequently than other sources, and Adobe’s July 2026 reporting showed those visits generated 53% more revenue per visit and converted at a 60% higher rate than non-AI traffic.
While consumers are increasingly willing to use AI to research products and guide purchase decisions, however, they remain significantly less comfortable allowing AI to complete transactions on their behalf. Both realities can coexist.
The opportunity for retailers lies in understanding where consumers embrace AI, where they hesitate, and how to bridge that gap to unlock growth. The retailers that engage customers through AI will be rewarded.
Where the hesitation shows up
Trust depends on what consumers are asking AI to do. Adobe found that 95% of consumers who turn to AI consider its responses at least as trustworthy as a traditional search engine, rising to 97% among regular users. Rather, the hesitation is narrower and more specific, and it grows as AI moves from suggesting to selecting to spending. As consumers move through their buyer journey they ask a more specific set of questions: How is my data being used? Whose interests shaped this recommendation? And how much control am I giving up?
Riskified’s quarterly tracker found that while AI became integral to product discovery, consumers’ comfort with agents making purchases fell from roughly 70% in late 2025 to just 45% by early 2026. Checkout.com reported 24% of consumers indicated they will never delegate purchases to AI. Further, in Alchemer’s 2026 retail report, nearly half of shoppers had used AI to research a purchase, yet trust in what it told them trailed both online reviews and word of mouth.
Why are consumers wary of how these tools use data, generate recommendations and exercise autonomy? The data points to a few key areas across various age groups.
- Privacy: How is the data behind personalized recommendations used, and who has access to it?
- Recommendation quality: Three-quarters of consumers say they would trust an AI agent less if its recommendations were swayed by brand dollars, and would trust the paying brand less too, according to Chain Store Age. That challenges the “retail media inside the agent” model many platforms are relying on for monetization.
- Control: Braze found only 10% of consumers are willing to let agents operate fully independently.
And while it’s true consumers readily use AI to explore their options, adoption drops sharply as they approach the transaction.
Winning trust
The gap between AI-assisted research and AI-driven purchasing represents one of retail’s biggest opportunities. Success will not belong to the companies that automate checkout fastest, but to those that earn enough trust for shoppers to let an agent act on their behalf.
Retailers that build transparency, control and accountability into their experiences will convert that trust gap into a lasting competitive advantage. Organizations should consider the following:
- Audit product data before buying technology: AI agents recommend what they can reliably evaluate. A system with a clean, protocol-compliant feed gets considered; a sophisticated system with poor data gets overlooked.
- Support the major AI protocols: ACP (Agentic Commerce Protocol), UCP (Universal Commerce Protocol) and MCP (Model Context Protocol) help connect merchants to the leading AI shopping and assistant ecosystems, making products available to AI agents and increasing their potential visibility. While protocol support creates access, recommendation success depends on accurate product information, strong content, and a compelling customer experience.
- Change what you measure: Sessions and bounce rate say little here. Track whether products appear at all on priority queries, where they rank and their share of AI-generated recommendations relative to named competitors.
- Win AI-assisted research before AI checkout: Roughly a quarter of shoppers use AI to decide what to buy, while almost none currently plan to purchase through them. Invest where the behavior already is.
- Make AI visible and personalization a choice: Privacy is the leading AI concern in every age group, and unlabeled AI reads as a hidden agenda. Personalization a customer has opted into feels helpful, not intrusive.
- Ground recommendations in sources shoppers already trust: Verified reviews and real purchase data provide credibility that helps AI recommendations earn consumer confidence.
- Rethink attribution for the agentic era: As AI agents increasingly complete purchases on behalf of customers, businesses need new ways to identify the channels, experiences and recommendations that created demand in the first place.
For more, read our industry outlooks for consumer goods, food and beverage, and retail and restaurant.
