The news: Consumers want AI shopping experiences but have little tolerance for failure.

• Two-thirds (66%) of consumers in the US and UK have shopped with a conversational AI assistant or are open to doing so, per Nosto.
• 20% have used genAI tools like OpenAI’s ChatGPT or Google’s Gemini for shopping, and 13% have interacted with an AI assistant on a brand website.

But while interest is present, trust is fragile: 69% of shoppers have walked away from their search altogether over irrelevant recommendations. Brands need to walk a fine line between providing an AI experience that feels personal and one that feels intrusive.

Digging into the data: Among consumers who find AI helpful, expectations focus on practical, low-friction value.

The most appealing use cases include alerts for discounts and price drops (59%), personalized recommendations (51%), and gift inspiration (44%). These features offer a competence check, helping consumers decide if AI can reliably save them time and reduce decision fatigue.

When these basics are executed well, confidence grows in letting AI handle more complex tasks.

• Almost two-thirds (61%) of all consumers and 88% who have ever tried shopping with an AI assistant would find it helpful if AI created product bundles or suggested complementary items.
• About half (48%) of all consumers would be willing to let AI build a full shopping cart for specific occasions. That number jumps to 81% among those who have shopped with an AI assistant before.

Why it matters: Retailers, however, may be underprepared to meet these rising expectations: Two-thirds of consumers are ready to engage or already using AI agents for shopping but only one-third (36%) of retailers have a dedicated AI budget.

When tailored to shoppers’ intent and interests, AI can help drive deeper engagement, guide shoppers toward decisions that increase purchase satisfaction, and act as an always-on sales associate.

Recommendations for brands: Those that move quickly to prioritize personalization and clearly demonstrate time-saving value will be best positioned to turn AI features into a trusted shopping partner.

• Allocate a budget to consumer-facing AI, including data infrastructure and personalization capabilities.
• Carefully test assistants before deployment, considering consumers’ low level of patience for unhelpful AI and the risk of cart abandonment.
• Select the underlying models for AI web features based on their ability to provide relevant suggestions and integrate cleanly with user data, rather than on brand recognition alone.

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