As with any disruptive technology, conversations surrounding generative AI have been polarized. Early adopters have put generative AI on a pedestal, treating it as an all-in-one tool for consultative guidance and creative inspiration, even emotional love and support. Detractors, meanwhile, have deemed AI a killer of creativity, a compressor of culture, and an enabler of simple, one-dimensional thinking. 

In the context of commerce, discussions have been equally divisive. Is generative AI a robust tool for customer sovereignty, empowering them to take control over their browsing and buying journeys? Or is AI merely farming traffic, pushing consumers towards the same set of brands and products? 

Using a two-phase survey methodology, we were able to better understand the distinct role of generative AI in the shopping journey. Due to their ability to analyze, synthesize, and streamline information, platforms like ChatGPT, Perplexity, and Gemini add a new dimension to commerce that combines aggregation, curation, and consultation. 

During our data collection and analysis, we found that the reality of consumers’ new browsing and buying behaviors is far more nuanced than industry discourse suggests. Indeed, AI isn’t just a fad or a hype cycle; it’s a new tool that is both democratizing and contextualizing information. They are finetuning the Information Economy that brought us Amazon, “The Everything Store.” And they are building upon the Curation Economy that emerged with the rise of algorithmically powered social platforms like Instagram. 

The result is the Concierge Economy, where artificial intelligence simplifies the abundance of content and information we’re forced to consume and interpret daily. These platforms are becoming personal concierges that eliminate the mental load of decision-making and streamline aesthetic creation. And they are completely changing the rules for how brands can and should show up.

‍

For the 2025 Holiday AI Shopping Benchmark, we partnered with Cimulate to run a two-phase survey of Gen Z, Millennial, and Gen X consumers, with each demographic pool equally represented. By excluding Boomers from the survey, we were able to set a more apparent benchmark for established and power-user behaviors. 

In each phase, we surveyed 1,000 US consumers to provide a statistically significant gauge of how AI platforms, such as ChatGPT, Perplexity, and Gemini, are not only influencing omnichannel shopping behaviors but also completely reframing how we engage in commerce.

For Phase 1, we asked the respondent pool pointed questions about their holiday shopping intentions and priorities. If they planned to use AI, how would they do so? Had they used generative AI platforms in the past? If yes, how did their experiences shape how they thought these tools could support their holiday shopping goals specifically?

Then, in the season’s wind-down, we surveyed an additional 1,000 US consumers to understand how they actually used AI to research, browse, and purchase holiday gifts. These respondents were selected exclusively because they not only used generative AI platforms regularly but also had a history of using them for shopping. Focusing on AI-native shoppers helped us better understand the long-term behavioral impacts for this segment. How did their interactions with AI shape what they believed to be an easy, fun, even meaningful holiday gift-shopping journey? And perhaps most importantly, how would their experiences ultimately shape their future online and in-store shopping? The goal was to clearly distinguish intent from impact and identify any breakdowns in the AI shopping experience that could affect consumers’ future use. 

From Experimentation to Habit Formation

In Phase 1 of this research, consumers told us something retailers weren’t ready to hear: AI was already part of their shopping behaviors, and they were already reaping the benefits. In fact, generative AI platforms are completely reframing the shopping journey, changing where people begin the process, how they decide what to buy, and what they expect from brands once intent is formed.

AI has become consumers’ most practical, personalized tool for discovery, comparison, and confidence-building. It is the new front door to commerce for high-intent, time-constrained, digitally fluent shoppers.

Awareness of AI platforms in Phase 1 of the research exceeded 80% across Gen Z, Millennials, and Gen X, and nearly 70% of consumers already used generative AI platforms regularly. AI has even crossed the familiarity threshold and entered the mainstream of consumer behavior, with 52% of respondents saying they used generative AI platforms to shop in the past.

What was more telling, however, was intent. Nearly half of consumers (49%) reported that they would likely begin researching gifts using AI during the holiday season. A quarter said they were very likely to do so. Consumers’ actual behaviors indicated greater favoritism toward AI, with 80% of respondents reporting that they first turned to AI platforms when researching gifts and holiday purchases. 

A meaningful share of shoppers now turn to ChatGPT, Perplexity, Gemini, and similar platforms before traditional search engines or retailer websites, which were once the most profitable first steps in the shopping journey.

Phase 2 tested that intent in real conditions. The following month of building lists, checking them twice, and checking them off helped validate and, in some cases, clarify where AI can really shine. It introduced urgency, budget pressure, gifting anxiety, and time scarcity. We didn’t ask consumers what they might do. We dug deep to understand the consumers who actually used AI to shop.

The New Front Door of Commerce

Consumers’ post-holiday reflection confirmed that AI is no longer something they test or tinker with. They reach for it (and trust it) in high-stakes moments, such as gifting and highly considered purchases. 

No clicking senselessly through results, hoping to find a relevant outcome. No more scrolling endlessly through lines of merchandise, hoping to be inspired. 

Phase 2 validated the predictions set in Phase 1. Our pre-holiday research suggested that AI was becoming a new front door to commerce, but our holiday post-mortem showed what happens when consumers actually walk through it.

Respondents used these AI platforms to find deals, generate product ideas and inspiration, and research specific products from brands. They offloaded curiosity, uncertainty, and comparison to AI and saw value in the outcomes, whether in time, effort, or money.

However, the most notable throughline connecting both data-collection phases is that this is not where consumers want to complete transactions (yet). The promise of agentic checkout may inspire some exciting theories and hypotheticals about the future of commerce. Still, consumers use AI tools more as destinations for aggregating options, synthesizing information, curating inspiration, and validating choices.

In Phase 1 of the research, 77% of consumers said that when a generative AI platform makes a product recommendation, they are more likely to click through to a merchant's website to continue researching or complete the purchase. Notably, in Phase 2 of the research, the same number of consumers reported applying these behaviors while shopping for gifts.

Despite industry chatter, AI platforms are not completely stealing conversions from merchants. But they are reshaping the funnel upstream. AI platforms conduct research, narrow options, surface trade-offs, and find the best deal, eliminating much of the work consumers once did across dozens of tabs and sites. Now, when shoppers land on a brand or retailer site, they arrive with higher conviction and lower tolerance for friction. This sentiment is especially strong during the holiday season, when consumers turn to AI to make their lives easier and more efficient. 

Deal-Hunting Fatigue Is the Behavioral Unlock

AI isn’t the primary checkout lane yet, but the promise of a great price does increase probability.

We asked consumers who used generative AI platforms whether offloading deal hunting to AI motivated them to complete a purchase within these destinations. The results confirm that when consumers can reduce the cognitive load of searching and comparing options, while also saving money, their adoption of embedded checkout surges. 

While recommendations would motivate only 23% of consumers to complete a purchase on an AI platform, 44% did so when the platform identified the best price for a specific product.

In Phase 1 of the survey, more than 57% of all consumers reported being so tired of hunting for deals that they wanted AI to handle price comparisons on their behalf. Among those who had experience shopping via AI, 60% have used it at least sometimes to find the best price on an item (22% always, 38% sometimes).

Consumers use generative AI platforms to save them time, money, and mental energy. For Millennials, who often juggle careers, families, and financial pressures, that number is even higher. Moreover, despite 31% of Millennials saying they’re “sick of AI being pushed on me,” the highest of any generation surveyed, 56% said they found the idea of AI-driven deal-hunting appealing. This cohort was also the most likely (59%) to purchase via AI from a new brand to get the best possible price. We saw these expectations carry over into reality. Breaking down use cases by demographic, Millennials were more likely than any other generation (62%) to use AI to find the best deals and prices. 

AI earns a seat at the table when it removes friction and ensures economic efficiency. When the value is clear, concerns around unfamiliar retailers or even new purchase paths recede into the background. 

From a strategic standpoint, this reframes AI’s so-called “killer feature.”

From the Curation Economy to the Concierge Economy

The most significant findings of this consumer research lie beneath the surface. They identify the layered, generational nuances that speak to how consumers view commerce as an extension and expression of their lifestyle. Commerce is part and parcel of existence. And how digital technology—especially AI—facilitates the curation, progression, and amplification of their identities.

For the most part, Gen Z and Millennial behaviors in Phase 2 of the research were mirror images of each other. Both segments used AI platforms most frequently to receive product inspiration for distinct needs, find the best deals on specific items, and compare similar products from different brands. These cohorts were also nearly twice as likely as Gen X to use AI for researching specific trends and aesthetics. They’ve assigned AI platforms the roles of curators and concierges. These platforms help curate users' tastes and visual identities, and also deliver the most relevant brands and products based on users' contextual needs and preferences. It’s automated identity formation. 

Gen X also primarily used AI for deal-hunting, but that was where the similarities ended. The oldest cohort primarily used AI to research specific products from specific brands (55%) and compare similar products from different brands (56%). 

In our New Modes survey, we found that Gen X consumers were more likely to spearfish while shopping. Armed with a specific need or idea, they were far less likely than their younger peers to shop on inspiration- and media-driven platforms like YouTube or Instagram. Instead, they gravitated towards marketplaces. This latest round of research not only validates these behaviors but also identifies AI as a viable tool to support their more precise shopping practices. 

The Trust-to-Utility Equation

Much has been made of trust as a barrier to AI adoption. The data provides additional context on how trust is earned and maintained among today’s consumers. Among consumers who have not yet used AI for shopping, the primary barriers relate to personal preferences and concerns about data privacy and bias.

Most Gen X (31%) consumers surveyed in Phase 1 didn’t use AI platforms to shop because they didn’t know which one was best for their needs. Despite being dubbed “the least loyal generation,” 38% of Gen Z consumers said they didn’t use AI to shop because they preferred branded experiences, much higher than their Gen X counterparts (30%). Gen Z consumers were most concerned about data security and bias (42%), with Millennials falling slightly behind (40%).

Looking at the broader dataset of current AI users and shoppers surveyed in Phase 1, AI fares surprisingly well when compared with other channels. Consumers reported trusting AI platforms as much as search engines (41%) and brand websites (37%). Some respondents even reported trusting AI more than social media (16%) and influencers (17%). 

Surprisingly, Gen Z shows greater trust in AI than in the content they spend so much time consuming. Up to 21% of these consumers said they trust AI more than social media, and one in five say they trust AI more than influencers, showing early signs of how younger consumers perceive social feeds laden with sponsored content and algorithmic noise versus an always-available, contextual Answer Engine. After years of navigating the flattening of culture and trend cycles that move at a breakneck pace, their fatigue is more apparent than ever.

But make no mistake, the consumers who use AI to shop, especially for holiday gifts, expect tangible value. That value is tethered mainly to consumers’ wallets.

‍

Where AI Wins (and Where It Doesn’t)

The data also clearly delineates which categories are most conducive to AI shopping. At Future Commerce, we believe that consumers are omnimodal. The channels they choose are based on their in-the-moment needs, goals, and contexts. Decisions are further shaped by their unique experiences, emotional triggers, and what consumers want from the shopping experience at that moment. 

Consumers surveyed in Phase 1 reported that they were most likely to use AI to research or purchase products when knowing product specifications led to better decisions. Electronics led the way, followed by apparel and accessories, toys and games, beauty, and home goods. These are categories in which information density is high, and differentiation could be rationalized.

During the holiday season in particular, consumers are focused on getting the best product at the best possible price; you can’t validate your decision thoroughly without the data to back it up. The second survey validated this value proposition, with most respondents using AI to research electronics, apparel, and accessories. 

Conversely, categories associated with symbolism, identity, and deep brand affinity, such as luxury and sporting goods, exhibited significantly lower AI usage. This bifurcation matters because it further contextualizes curatorial habits. When consumers said they used AI to research specific trends and aesthetics, there was a clear goal to obtain product recommendations associated with those trends and aesthetics.

For instance, if a Gen Z consumer were gift shopping for her best friend who is into the “clean girl” aesthetic, the ideal output would be a curated list of “top brands and products for clean girlies,” including rich product details, pricing information, inventory levels, and detailed breakdowns of where to find each item at the best possible price.

These results also point to opportunities for all brands and retailers. For those in AI-strong categories, content must answer questions by focusing on structured data, detailed attributes, comparisons, and clear value propositions. In categories where AI is used less frequently, content must create desire through storytelling, worldbuilding, and emotional resonance. It should help contextualize the brands and products through a trend and aesthetic lens. Using words and phrases that align with relevant trends and aesthetics can ensure brands are included in the mix and then stand out from the final list of options. Brands must understand the role AI plays for consumers when they shop in their category, then plan and design accordingly.

Reawakening eCommerce

When you have all of the world’s brand and product options at your fingertips, and everything is organized, categorized, and prioritized for you, what benefit do branded environments bring? And are the benefits of those experiences enough not to sway future behaviors?

Our goal was to further examine these questions and compare consumers’ anticipated behavior shifts before and after using AI to support holiday gift shopping.

The good news is it’s improbable that eCommerce experiences will see cannibalization. In Phase 1 of the research, only 10% of consumers reported that using AI to shop for the holidays this year would reduce their visits to branded eCommerce sites. That number barely changed (11%) in Phase 2. However, slightly more (14%) consumers in Phase 1 said they would visit marketplaces, such as Amazon, less frequently, and that number increased to nearly 20% in Phase 2. 

The most interesting shift was found when we dug deeper. We found a wealth of information when we examined how consumers planned to use eCommerce sites in the future.

Consumers who had firsthand experience using AI to shop for gifts further realized the value of eCommerce sites as a source of inspiration (up from 12% to 19%). This shift proves that AI isn’t cannibalizing business from these sites; it’s just redefining what these spaces are for. 

eCommerce websites shouldn’t be cookie-cutter landing pages with digital aisles of one-dimensional product images. They should be branded destinations where decisions are confirmed, trust is won, and relationships are nurtured through robust storytelling and worldbuilding. Product imagery and data are further contextualized with a brand’s distinct point of view and expertise. AI certainly narrows the pool of options, leading consumers to click through to fewer sites and visit less often. However, it does not eliminate high-intent, highly engaged consumers who are more likely to explore and convert.

The Unexpected AI Casualty: Physical Retail

Merchants may not be ready for one key finding from the surveys: AI’s impact on store foot traffic. Just as merchants must consider the value of their branded eCommerce sites, they must determine the value of brick-and-mortar spaces, whether it is a pop-up, shop-in-shop, a big-box retailer, or an immersive branded environment. 

What value will visiting a store provide consumers? Some branded storefronts don’t just bring breadth and depth of inventory; they also offer meaning, community, and belonging. For others, stores are just one-dimensional vessels for products, which gives shoppers more reason to stay home on the couch, consulting their chatbots. 

When asked how using AI to plan holiday shopping would affect their behavior, 30% of Phase 1 respondents reported they would visit physical stores less often. That number increased to 40% in Phase 2, a statistically significant increase that exceeded consumers’ planned changes in online shopping behaviors, particularly toward branded sites. AI threatens physical retail nearly four times more than branded eCommerce. 

Gen Z was more likely to curb their store visits in Phase 1, with 36% saying they expect to visit stores less after holiday shopping with AI. However, in Phase 2, these self-identified shifts remained stable among Gen Z and then increased significantly among older age segments.

Given Millennials’ unique life stage, where they’re juggling work responsibilities, children’s school and sports schedules, and aging parents, it makes sense that this cohort is feeling the mental squeeze of being the “Chief Home Officer” and is looking to offload tasks and decision-making whenever possible. However, the most striking shift was observed among Gen X respondents: while Phase 1 respondents expected only 26% fewer store visits, this figure increased to 40% in Phase 2. 

With firsthand experience using AI during the holiday season, consumers of all ages plan to make fewer visits to stores. 

For decades, brick-and-mortar retail’s value proposition has rested on discovery and comparison: the ability to easily look at two items side by side and make an informed decision. AI now performs these functions faster, cheaper, and from the couch. These results don’t invalidate the value of brick-and-mortar itself. If anything, they confirm just how critical other components of the experience are. Unless stores offer something meaningfully different, such as access to community, high-value service, or cultural experiences,  they risk losing relevance in the critical top and middle stages of the funnel altogether.

AI may remove the need to wander, but it doesn’t eliminate our innate need for authentic human connection and belonging.  

The Self-Awareness Divide: Breaking Down Generational Nuances

The most meaningful difference in generational AI shopping behaviors isn’t frequency of use nor categories shopped; it’s self-awareness.

Across both phases of this research, Gen Z emerges as the cohort most aligned with its own behavior. What Gen Z consumers said they would do in Phase 1 closely mirrors what they actually did in Phase 2, and what they plan to do in the future. Their personal intuition, coupled with their knowledge of digital technology and eagerness to tinker with new platforms, makes them (by far) the most self-aware consumers in the AI era. They understand their triggers. They recognize when values matter, and when constraints override them. As a result, their behavior remains comparatively stable across contexts, even as tools and channels change.

Millennials and Gen X, by comparison, show larger intent-action gaps. In Phase 2, both groups were significantly more likely to accept deals from unfamiliar retailers than they had anticipated in Phase 1. Price sensitivity asserted itself more forcefully than brand preference once AI made alternatives easier to see and compare.

There is nuance, though. Millennials and Gen X appeared not to fully grasp AI’s benefits until they rolled up their sleeves and applied relevant, meaningful use cases. Returning to consumers who did not use AI to shop, the largest share of respondents who “didn’t know which platform was best” were in the Millennial and Gen X cohorts. Many of them are likely still learning the value of these platforms and how to craft prompts that lead to the best answers. 

The consumers surveyed in Phase 2, across all generational cohorts, crossed the chasm as they tested, learned, and shopped with AI during the holiday season. 

The implication is not that older generations are less rational shoppers. It is that AI exposes behavioral truths that consumers are often poor at predicting about themselves.

Gen Z, having grown up inside algorithmic systems, appears more fluent in this reality. They are not surprised by their own tradeoffs. They plan for them.

In an AI-mediated commerce environment, self-knowledge becomes a competitive advantage.

What it All Means for Brands and Retailers

Discovery now occurs through answer engines, but with 77% of consumers clicking through to eCommerce sites from AI platforms, merchants risk being excluded from the consideration set entirely if they’re invisible to AI-mediated discovery.

This research has clear strategic and tactical implications that profoundly impact teams across marketing, creative, digital, and operations.

• Simultaneously design for machines that curate and humans who seek meaning. Provide the rich, accurate, and structured data that engines need to trust and validate your brand and/or product. This includes product specifications, ingredients, product availability, pricing, and aesthetic information. Landing pages for AI traffic should mirror the specificity of the query that produced them.
  ‍
• Ensure branded eCommerce sites provide the value that AI can’t. AI can gather information, research, and surface answers, but it can’t fully convey a brand’s lore or create belonging. That remains the domain of human-centered brand experiences.
  
  
• Continue the concierge experience. Generative AI platforms are so effective because they provide concierge-level support through contextual conversations. The high-intent shoppers who come from these platforms to your site require the same level of service and experience. Branded chatbots and co-pilots can continue the conversation, asking proactive and thoughtful questions that help shoppers find the product and service they’re seeking. 

The future of commerce will be shaped by brands that design for both data-rich environments that machines can trust and immersive, contextual experiences that humans want to return to and share.

AI may be the front door to commerce. But what happens after someone walks through it is still up to brands. That is where the real opportunity lies.

‍

‍

‍

‍

‍

‍

‍

‍

‍