Consumers are still concerned about privacy, but they have more comfortable business data for better product recommendations. Share a little about what you viewed or purchased, and the experience becomes faster and more relevant.
But this openness has limits, and when brands go beyond what seems fair or transparent, trust quickly diminishes.
To improve recommendations, 43% of U.S. shoppers say they will share their browsing history, 42% their past purchase history, and 34% their location, according to Omnisend’s “AI Shopping Report.” This is a significant level of openness, but one that comes with clear expectations for how the data is used.
AI-driven purchasing is a simple exchange. Consumers share data in exchange for better recommendations, faster decisions and less friction.
What data would you share to improve recommendations?
Relevance drives data sharing, but not without limits
People will share data when the gain is clear. Behavioral signals such as browsing and purchase history seem acceptable because they directly improve the experience and accurate recommendations encourage them to share more.
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This change increases consumer trust in AI search results. According to Omnisend, 42% of U.S. shoppers say ChatGPT provides better product recommendations than traditional search engines, signaling a shift away from search in favor of recommendation-based discovery.
But willpower diminishes when the connection to value is unclear. Social data still feels personal, and consumers are much less comfortable sharing it for personalization.
Trust breaks down at specific times
Trust in AI shopping is not abstract. It breaks at predictable points and the data clearly shows those lines.
Personalized pricing is most important. Seventy percent of shoppers say they would opt out, stop purchasing, or leave negative reviews if they were charged differently for the same product.
There are also concerns about how recommendations are generated. About 28% of consumers are concerned that AI favors sponsored products, and 28% wonder if the results are biased or irrelevant.
Control is another pressure point. Thirty-four percent of shoppers are uncomfortable with AI making purchases without approval, and 45% are uncomfortable with how their data is collected and used.
What is your biggest concern about AI in online shopping?
AI becomes a new layer of influence
AI is already shaping purchasing decisions, although it has not replaced human intervention. Omnisend found that 18% of U.S. consumers prefer AI-generated recommendations over those from friends or influencers.
This figure is still low, but it could be a sign of a huge change. For these consumers, the choice of AI supplants search rankings and social proof. AI-generated recommendations become another place where brands clearly show up or are overlooked.
If this share increases, it will lead to big changes in the way marketers think about traditional channels like paid search, organic search and influencer marketing.
Clarity and control determine what happens next
The important thing to remember is not the advancement of technology. It’s about how clearly it’s explained and how much control consumers feel they have.
Consumers want to know what data is being used and why, understand why they are seeing specific recommendations, and maintain the ability to approve decisions before purchasing anything.
This is where many implementations fail. Even if recommendations are accurate, a lack of transparency or oversight can undermine trust and reduce adoption.
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What this means for marketers
Disclosure has become part of the experience. As concerns about sponsored endorsements increase, it is necessary to clearly label paid placements to maintain their credibility.
The broader change is simple. Consumers will share data and rely on AI when the value is clear, but they expect boundaries to be respected.
Success will depend less on how much data is collected or how advanced the models are, and more on whether the experience feels fair, understandable, and within the user’s control.
The full Omnisend report is available here. (No registration required).
Key Takeaways: AI-powered
- Consumers are willing to share behavioral data when it clearly improves recommendations
- The transition from research to recommendation is already underway
- Trust breaks down at specific moments, particularly around pricing, transparency and control.
- AI is emerging as a new layer of product discovery alongside search and social.
- Clear explanations and user control are more important than technical sophistication
