Imagine losing 19%–32% of your customers: How AI disrupted holiday shopping

Few retailers can face losses at this scale without feeling the impact. When AI fails to earn trust, the level of customer attrition is high. As AI moves from a supporting role into the center of the customer journey, challenges rarely stay isolated. When fairness or transparency breaks down, the impact is evident in customers who simply don’t return.

That’s a critical distinction from where this conversation started just a few months ago. Back in October, we published the AI Holiday Shopping Trends 2025 survey, which captured how shoppers expected to use AI during the holidays, where they saw potential, and what they hoped the technology would improve. Now, with the season behind us, the Post-2025 Holiday Shopping Survey reflects something far more valuable: what actually happened when AI was put to work at scale, and how those experiences are shaping customer trust moving forward.

The results provide a clear picture of the time shoppers spent, their level of confidence in their decisions, and how they evaluated the brands behind those interactions. The data highlights meaningful gains in efficiency and support, while also revealing big expectations around trust and transparency.

When AI gets it wrong, the cost is immediate.

24% of shoppers received what they considered a biased product recommendation from an AI chatbot, often based on stereotypes. The fallout was immediate:

• 32% lost trust in the brand.

• 27% said they wouldn’t recommend the brand.

• 19% said they would not shop with that brand again.

The implications of these numbers tend to show up later, as customers make different choices about which brands deserve their loyalty.

Transparency also plays a role in how customers make that decision. When shoppers weren’t told they were interacting with an AI agent, 40% said they felt misled. Another 45% felt neutral, which in retail customer experience usually means uncertainty rather than acceptance. If trust and transparency aren’t built into AI strategies from the start, retailers aren’t risking a small percentage of customers; they’re risking two to three out of every ten. This degree of attrition has lasting consequences for most retailers.

Shoppers trust AI more than ever before. This past holiday season, 89% of shoppers used AI in some form, consistent with last year. But usage alone doesn’t explain the shift. What changed is the extent to which AI influences decisions.

Only 1% of shoppers said AI chose gifts badly, while nearly one-third said AI chose gifts better than they would have themselves. Earlier in the season, shoppers talked about how they planned to use AI. After the holidays, the data tells us that people relied on it. They let AI narrow options, guide purchases, and reduce uncertainty. When customers trust AI to decide, they also transfer accountability. Any bias, poor judgment, or lack of disclosure isn’t seen as a technical issue but rather a brand failure.

AI delivered on its biggest promise: Efficiency at scale.

Despite the risks, it’s important to be clear about one thing: AI delivered real value this holiday season. The most significant breakthrough wasn’t novelty or personalization. It was efficiency. 74% of shoppers said they spent less time shopping because the experience was more efficient—a new and telling data point.

When we look closer:

• 43% saved 1–3 hours.

• 26% saved 4–6 hours.

• 7% saved more than 6 hours.

That’s not a marginal improvement. That’s a fundamental change in how people experience shopping during the most stressful time of year. For years, retailers focused on speed at the transaction level, prioritizing faster checkout, faster shipping, faster support. What this data shows is that time saved across the entire journey matters far more. AI reduced the mental effort of searching, comparing, and second-guessing. It helped shoppers move forward with confidence instead of hesitation.

This is one of the clearest examples of how AI is disrupting shopping: not by making it faster, but by making it lighter.

Time saved changed how shoppers felt and behaved.

Efficiency changed behavior and emotion. Among the 57% of shoppers who said AI improved their holiday shopping experience, the reasons were consistent:

• 66% said shopping felt less stressful.

• 65% said it was easier to find deals or savings.

• 48% said recommendations were more personalized and relevant.

• 43% reported receiving faster support or service.

These numbers show meaningful progress, but there’s still room to improve. Fewer than half felt recommendations were truly personalized. Less than half cited faster service as a defining benefit. That’s an important signal. AI-powered shopping experiences are reducing friction, but relevance and judgment still matter. The same systems that reduce stress can quickly create it if they feel careless, biased, or opaque. Efficiency earns trust. It doesn’t replace it.

AI saved shoppers money, but the impact isn’t universal.

AI also delivered tangible financial benefits, though this is where nuance matters most. Shoppers estimated their savings as follows:

• 30% saved $51–$100.

• 29% saved $101–$250.

• 13% saved $251–$500.

On the surface, the numbers are impressive. But without context, they’re easy to misinterpret. We don’t have granular insight into baseline spending. Someone who believes AI saved them $300–$500 was likely already planning to spend significantly more. For higher-income households, those savings may be incremental.
For low- to mid-income households, however, $251–$500 can represent an entire holiday budget. This is why discussions about how AI is disrupting shopping need to take into account income and context. AI affects every demographic and every wallet, but not in the same way. Retailers should be cautious not to overemphasize headline savings numbers without understanding who those savings truly benefit.

AI disrupted holiday shopping by proving its value.

AI proved its value this holiday season; now it must prove its integrity. It saved time, reduced friction, and helped shoppers feel more supported during one of the most stressful shopping periods of the year. Shoppers felt the improvements and adjusted their expectations accordingly. As AI impacts more parts of the shopping journey, tolerance for mistakes becomes narrower.

AI in retail will not be defined by adoption or capability alone. It will be shaped by how retailers design for trust, transparency, and judgment at scale. Efficiency may earn customer attention, but trust is what brings them back. And as this post-holiday data makes clear, losing even a fraction of that trust can quietly reshape a business in ways that are difficult to reverse.

AI has moved beyond experimentation. The question now is not whether it works, it does, but whether retailers are prepared to use it responsibly, consistently, and in ways that drive long-term relationships with the customers who rely on it.