The Mirror Cracks: Consumers Reject AI Digital Twins in Retail

PITTSBURGH, PA – December 03, 2025 – In the relentless pursuit of personalization and efficiency, the retail industry has embraced artificial intelligence as its ultimate co-pilot. Yet, a groundbreaking new study suggests that one of AI’s most ambitious applications—the creation of “digital twins” to simulate customer behavior—may be leading brands not toward greater intimacy, but into a trust crisis of their own making.

New research from retail technology firm First Insight reveals a stark disconnect between the industry’s tech-forward strategy and consumer sentiment. While retailers invest in building digital replicas of their shoppers from a trail of data crumbs—past purchases, browsing history, and inferred preferences—their customers are responding with suspicion and outright rejection. The findings serve as a critical warning: the line between insightful personalization and perceived surveillance is dangerously thin, and many brands may be about to cross it.

The Trust Deficit: A Digital Reckoning

The core of the issue lies in a fundamental violation of the customer relationship. According to First Insight's survey of over 1,300 U.S. consumers, a staggering 69% would trust a brand less if they knew it was relying on digital twins instead of soliciting real, direct customer feedback. The problem is compounded by a lack of awareness, with nearly half (48%) of consumers admitting they had never even heard of the term before.

Once the concept was explained, the reaction was swift and negative. The study found that 77% of consumers value authentic, direct communication from brands far more than the efficiency that automation might offer. A clear majority (55%) of shoppers prefer that brands simply “directly ask me” about their preferences, while a mere 8% are comfortable with AI simulation making those assumptions for them.

This isn't a simple preference; it's a foundational expectation of respect and consent. When brands choose to simulate their customers instead of engaging with them, they are not seen as innovative but as dismissive. The data suggests that this shortcut to understanding the customer paradoxically leads to alienation.

“When retailers cut customers out and rely on synthetic replicas instead, trust collapses. You cannot claim to know your customer while replacing them with a model of themselves,” said Greg Petro, CEO of First Insight, in the press release accompanying the findings. “Consumers aren’t anti-technology, or anti-AI, they’re anti being modeled, simulated and monetized without their consent.”

Beyond the Hype: The Hidden Commercial Costs

While the erosion of trust is a significant brand risk, the commercial implications are more immediate and severe. First Insight's data indicates that 58% of consumers would become brand detractors upon learning they were being modeled without consent—either by ceasing to recommend the brand or by actively warning others against it. Forty-two percent would go a step further, significantly losing trust or stopping purchases entirely.

This backlash is most pronounced among the highest-spending demographics. A majority of Baby Boomers (58%) and a significant portion of Gen X (42%)—cohorts that drive substantial revenue in key sectors like apparel, home goods, and CPG—are the most likely to walk away. For retailers, this represents a direct threat to their bottom line.

The irony is that the market for digital twin technology is booming, projected to swell from $2 billion in 2025 to over $12 billion by 2033. Its applications in optimizing supply chains, store layouts, and inventory management are well-documented, with giants like IKEA and Walmart leveraging the tech for major operational gains. The controversy begins with the specific application known as the “Digital Twin of the Customer” (DToC), a virtual proxy intended to anticipate behavior. Even industry analysts like Gartner have noted that while the concept holds promise, its adoption is significantly hampered by the very issues First Insight's study highlights: customer trust and data privacy concerns.

Gen Z's Ultimatum: The Activist Consumer

If older generations react by quietly taking their business elsewhere, Gen Z is poised to lead a much louder, more organized resistance. The study reveals that today’s youngest adult consumers, while digitally native, are fiercely protective of their autonomy and deeply skeptical of corporate overreach. While 24% of Gen Z were initially comfortable with digital twins, that sentiment evaporated once the implications of unconsented use were explained.

After learning more, 59% cited lack of consent as a primary concern, and their potential actions are a modern-day brand manager’s nightmare. A majority (54%) said they would switch brands entirely, 53% would post about the practice on social media, and 52% would go so far as to encourage boycotts. They are not just passive consumers; they are active participants in brand narratives, and they are prepared to rewrite the story for brands that cross their ethical boundaries.

This generation's reaction underscores a critical shift in consumer expectations. For them, transparency is not a bonus; it is the price of entry. Authenticity is not a marketing buzzword; it is a demand. Brands hoping to capture this demographic's loyalty must understand that engagement cannot be simulated; it must be earned through genuine, two-way dialogue.

Navigating the Ethical and Regulatory Minefield

The consumer backlash detailed by First Insight is not occurring in a vacuum. It aligns with a rapidly solidifying legal and ethical framework around data privacy. Regulations like Europe’s GDPR and California’s CCPA already place strict limits on profiling and automated decision-making, mandating transparency and user consent. With nearly two dozen U.S. states having enacted their own privacy laws and AI-specific legislation on the horizon, the regulatory risks for companies using DToCs are escalating.

Beyond legal compliance lies the ethical minefield of algorithmic bias. AI models trained on historical data risk perpetuating and even amplifying societal prejudices, leading to unfair pricing or exclusionary product recommendations. The “black box” nature of many complex algorithms makes it difficult to ensure fairness and accountability, further eroding the fragile trust between a brand and its customers.

Retailers now stand at a critical crossroads. One path leads toward deeper reliance on opaque, simulated models of their customers—a path of perceived efficiency paved with profound reputational and commercial risks. The other path requires a more deliberate, human-centric approach: using AI not to replace the customer's voice, but to amplify it, fostering a new kind of loyalty built on transparency, consent, and authentic engagement.