The news: Checkout is becoming AI’s clearest consumer-facing ROI case in retail.

• 42% of US consumers want faster checkout and call it their No. 1 priority, and 48.2% will avoid a store because of checkout delays, per VoCoVo’s “In-Store Intelligence” report.
• More than one-third of US retail decision-makers want to address this: 38.9% call faster checkout their strongest motivator for AI adoption and investment.

However, there’s a disconnect between both parties around AI use for theft reduction.

• 33% of retailers use AI to reduce theft, and 52% plan to adopt anti-theft AI tools within 12 months.
• By contrast, nearly 80% of consumers are unsure how AI is used in stores and are uncomfortable when it feels like surveillance.

Zooming out: Checkout optimization can become a retention and revenue issue. The strongest implementations may be AI that consumers barely notice and can comfortably quantify—shorter lines, fewer checkout bottlenecks, and better inventory information—rather than conspicuous AI experiences.

Consumers want AI that makes existing operations work better, rather than more AI experiences overall. That favors investments tied to measurable customer experience improvements—not novelty.

The conflict: As AI infrastructure grows around applications like computer vision, retailers need to consider what they do with resulting shopper data, whether that’s securing it to avoid customer scrutiny or taking a chance with consumer trust and using it for personalized experiences.

Companies that figure out how to implement AI to remove user friction without alienating shoppers could gain both brand loyalty and operation efficiencies.

Recommendations for retailers: Prioritize invisible, accepted AI uses like faster checkouts and up-to-date inventory information online that offer measurable benefits for existing customers. Explore consumer-facing AI tools like push-buttons in aisles with AI assistants that can answer user questions about products or inventory.

Slowly introduce any AI-backed theft-reduction practices to evaluate consumers’ reactions, and offer clear explanations on websites and in-store on how and where data is used. Weigh the benefits of surveillance against the risk of losing user trust.

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