Artificial Intelligence

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AI adoption is accelerating faster than almost any technology in history. But consumer trust is moving in the opposite direction. According to Capgemini research, one-third of consumers now spend more than an hour a day with AI tools, yet overall trust in AI has dropped from 72% to 58% in the past year. That gap is the strategic problem. Retailers who close it first will own the next era of brand loyalty.

Why the disconnect?

Consumers aren’t rejecting AI. They’re rejecting a lack of transparency. According to a recent survey from my company, Prosper Insights & Analytics, 32% of respondents stated the need for more disclosure on the data it uses as a top concern about recent developments in AI.

For example, when people use AI as a shopping assistant or turn to it for product/service recommendations, they’re making a decision on which tool they use, what information they provide, and whether they trust the output. But in retail, most consumers lack visibility into how their data is used, how algorithmic decisions are made, or who’s accountable when things go wrong.

As Dreen Yang, Head of Consumer Products & Retail at Capgemini puts it, “Consumers don't expect AI to be perfect. They expect honesty about what it does, what it doesn't do, and who they can talk to when something goes wrong. That's the bar right now. The brands clearing it aren't the most technically advanced. They're the most transparent."

Capgemini’s research finds that over half of consumers want explicit controls over their personal information in AI systems. Not just opt-out mechanisms, but genuine human-in-the-loop governance. This need for transparency runs deeper than most brands realize. Research from IDPC found that 61% of people are concerned about how AI systems use personal data, reflecting widespread unease about how information is processed, shared, and ultimately influences decisions behind the scenes.

The real stakes for brands

For retailers, this creates an unusual opportunity. While much of the tech industry is racing to deploy AI, a meaningful competitive advantage belongs to brands that get the trust equation right first.

In fact, according to Capgemini’s research, AI has already replaced traditional search engines for half of consumers. Similarly, “searching on the internet” is the most popular use for Gen AI according to a recent Prosper Insights & Analytics survey. That’s a significant market shift. But here’s what matters: consumers are increasingly willing to pay more for security and privacy safeguards to be built into the experience. That willingness to pay is a concrete signal. Brands that build privacy into the experience, rather than bolting it on after the fact, have pricing power their competitors don't.

What leadership looks like in practice

The mistake many brands make is treating trust as a messaging problem rather than a systems problem. According to Dreen Yang, true trust-building requires three concrete moves:

• “First, be transparent about trade-offs. Every AI system makes choices: speed versus accuracy, personalization versus privacy, convenience versus control. The brands getting this right say something like, 'This system personalizes your experience by analyzing your browsing behavior. You can turn it off here. Here's what changes if you do.' That's respect. Customers respond to it.”
• “Second, accountability structures. Consumers want to know who to contact when something goes wrong. Not a bot. Not a chat window. A human decision-maker. In sectors where consumers understand the governance structure, trust holds steady even as AI deployment scales.” This is supported by research from Verizon which found that 47% of consumers report high frustration when they’re unable to quickly access a human agent when needed, and those moments create permanent loss of trust in that retailer.
• “Third, data minimalism. Most organizations still collect as much data as possible 'in case we need it.' Flip that. Collect only what you need for the specific function, delete it on schedule, and tell customers you're doing it. Less data collection builds more trust than elaborate privacy policies. That's not a paradox. It's just how trust.”

Generational nuance matters

IDPC finds that Gen-Z leads in AI adoption but also in skepticism about its governance – they use AI tools and demand transparency simultaneously. Gen-Z’s simultaneous embrace and skepticism of AI isn’t contradiction, it’s maturity. They grew up with algorithmic systems; they understand that tech is neither inherently good nor bad. They just want the best version of it.

As Dreen Yang notes, “Gen-Z doesn't see AI as exciting or threatening. They see it as infrastructure, as routine as email. But that familiarity makes them sharper critics, not easier customers. They notice when an AI system is making unfair trade-offs or collecting data it doesn't need. And they walk away from brands that assume they won't.”

The insight here is that younger audiences reward brands for being honest about how and where they use AI. A brand that says “We use AI to recommend products, and here’s why we think that serves you better. You can turn it off here,” will outperform a brand that obscures or oversells its AI features. What works is candor: acknowledging both what AI does well and where it falls short.

This is why some of the most interesting brand positioning right now comes from companies being explicit about what they’re not doing with AI. That's not a retreat from AI. It's a positioning choice that reflects where consumer trust actually forms.

Brands can define trust standards before regulation does

Guardrails aren’t obstacles to AI adoption; they’re prerequisites for consumer trust. Ultimately, customers want AI innovation to continue within a framework. Brands can either wait for that framework to be mandated externally or build it internally and market it as differentiation.

The brands that treat trust-building as strategic will find that adoption and confidence in AI aren’t in tension. They’re two sides of the same coin. AI systems people understand and control are the ones people use most.

Regulation will eventually codify what the best brands are already doing. The advantage belongs to the retailers who set trust standards now, on their own terms, rather than waiting to comply with someone else's framework.

Disclosure: The consumer sentiment study referenced above was conducted by my company, Prosper Insights & Analytics. This is the same dataset used by the National Retail Federation, and available from Amazon Web Services, Bloomberg, and the London Stock Exchange Group for economic benchmarking.