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In 2026, the race to capture consumer data has intensified as AI expands across industries. In this environment, data privacy is increasingly being framed as a luxury—something that not all consumers can access or afford to prioritize.
Consumer-focused AI applications are emerging in both online and offline retail. Tech companies are seeking detailed information about individuals, ranging from personal preferences to behavioral patterns observed through store visits. Many of the promises for AI in shopping—such as ultra-personalized recommendations and in-store services designed to anticipate customer needs—depend on collecting as much data as possible.
Companies such as Meta and Google continue to pursue new ways to gather more data, in part because much of their revenue still comes from advertising. To support this, tech giants are investing heavily in data storage infrastructure, with year-to-year spending up 77%, reaching a record $725 billion this year. As AI makes personalization in advertising and customer service more widespread, both tech companies and brands face pressure to hold more data to compete.
At the same time, customers are showing fatigue about the amount of data they are asked to share and whether the exchange of personal information is worth the benefits received. Affluent and educated consumers are increasingly taking steps to defend privacy by declining data collection, targeted advertising, or subscribing to encrypted digital services. This shift creates a challenge for luxury brands that differentiate themselves through premium, highly personalized customer experiences.
“This is a very fine line brands must balance, because there are huge business benefits involved, but more and more people recognize the abuses that have occurred and are occurring,” says Carol Aquino, Director of Consumer Tech at WGSN.
In Vogue Business’s AI survey, privacy concerns and how fashion companies use AI rank as the fourth-largest worry among participants. As consumers grow tired of dense targeted ads and highly personalized social media experiences—an AI-driven trend—privacy is becoming a more prominent cultural and societal issue.
The trend is also contributing to business-model shifts in social media, moving some users from free, ad-supported platforms toward paid, ad-free packages. YouTube, Instagram, Snapchat, and Facebook have each launched paid subscription options that allow users to browse without ads, with the approach funded by monetizing user data.
Tech companies often argue that AI can deliver consumer benefits, including shopping chatbots with more precise recommendations, deeper health analytics, and device use without looking at a screen. Patricia Egger, Head of Security at Proton, emphasizes that data sensitivity should determine how it is handled.
“Not all data is equally valuable—sensitive data such as health information must be protected more strictly, while shopping data may be acceptable if used to monetize,” says Patricia Egger.
“If you’re not paying with money, you’re paying with your data—yet how you choose to pay is something users should decide.”
Beyond paid subscription models, high-income consumers are increasingly seeking brands that treat privacy as a competitive advantage. One example cited is Even Realities’ smart glasses, which are positioned as not raising surveillance concerns. The product includes a health-tracking ring, but the glasses themselves do not include a camera—an approach CEO Will Wang says differentiates it from competitors such as Meta.
Pricing for the Chinese brand starts at $599, while Meta’s mainstream model sells for up to $379. Wang argues that the privacy cost of camera integration is high relative to the evidence of its real value.
“Thus far, there is not much persuasive evidence of the real value of camera integration in glasses, while the privacy price to pay is very high. Therefore, we want to pursue a direction more socially acceptable—more cautious with the data we collect,” Wang notes.
He adds that most Even Realities customers are high-net-worth individuals or people active in politics and with public influence.
“How we value privacy and user data is received positively by this client base. I think it’s important to view it as part of the user experience—clearly explained terms, what data is collected and why; and giving users many opportunities to opt out,” he says.
While analysts expect AI to improve the quality of customer guidance in stores, the article suggests that brands maintaining a data-intensive sales model focused on relationships may find stronger resonance with high-end customers.
The content also highlights how AI is spreading beyond core commercial uses, including applications aimed at supporting older people at risk of dementia, and consumer-facing uses such as AI-assisted content distribution and AI-enabled toys. These examples underscore the wider expansion of AI in everyday life, alongside ongoing questions about data usage and privacy.
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