The AI Shopper is Already Here: What 1,000+ US Online Shoppers Tell Us About Behavior Change in 2026

For most of the past decade, online shopping has been a search-driven activity. Customers came to retailers through search engines, paid ads, and brand-direct traffic; they evaluated products through retailer-controlled discovery interfaces; they bought through funnels engineered around predictable decision patterns. The customer behavior model that retailers planned around was the search-engine shopper.

That model is changing fast. Locus’s Q2 2026 US Consumer Survey of 1,000+ active US online shoppers reveals that 45% now use AI tools like ChatGPT and Claude as part of their shopping journey: to discover brands, compare products, summarize reviews, evaluate value propositions, and make purchase decisions. The customer who used to type a query into Google now types it into a conversational AI; the customer who used to scroll through retailer category pages now asks an AI to surface options. The behavior change is not happening at the edges of online shopping; it is happening at the mainstream.

The survey reveals three specific behavioral shifts that retail and e-commerce executives need to plan for: AI has become a mainstream shopping tool (45% adoption), AI expands brand consideration sets (39% of AI users try new brands), and AI drives larger baskets (37% of AI users buy more per order). Each shift is individually significant; together they describe a customer that retail operations built for 2024 cannot serve optimally.

For CMOs, CXOs, COOs, Heads of E-Commerce, and retail executives navigating 2026, this is a framework covering the three shifts, what the survey data reveals about each, and the cross-functional implications retailers need to address.

Shift 1: AI Has Become a Mainstream Shopping Tool

The finding. 45% of US online shoppers in the Q2 2026 Locus survey report using AI tools as part of their shopping journey, either as primary or secondary tools. The 45% figure crosses a critical mainstream threshold. AI shopping is no longer the behavior of early adopters; it is the behavior of mainstream consumers.

What this means in practice. The customer journey that begins on an AI conversation rather than a search engine produces different patterns from start to finish. Discovery happens through natural-language interaction rather than keyword search. Product comparison happens through AI-summarized analysis rather than retailer-side-by-side feature lists. Review evaluation happens through AI summarization of consumer sentiment rather than customer reading individual reviews. Purchase decisions are reached through conversational dialogue rather than through funnel optimization. The customer arriving at the retailer’s checkout has navigated a different journey than the search-driven customer of three years ago.

Why the 45% threshold matters strategically. Marketing strategies, e-commerce funnels, and customer experience designs calibrated to search-engine shoppers do not optimize for AI-assisted shoppers. SEO investments produce diminishing returns when nearly half of customers reach products through AI summarization rather than search ranking. Paid search budgets compete for an increasingly smaller share of buyer journeys. Product detail pages designed for human scrolling and feature comparison serve AI agents that read structured data differently than humans read marketing copy. The 45% finding is not a marginal trend; it is a structural change in how customers reach retailers.

AI is reshaping shopping behavior across three dimensions: 39% of AI-assisted shoppers try new brands they wouldn’t have considered, and 37% buy more items per order. Brand consideration is reshuffling, and basket economics are changing simultaneously.

Shift 2: AI Expands Brand Consideration Sets

The finding. 39% of AI-assisted shoppers in the Q2 2026 Locus survey report being more likely to try new brands they wouldn’t have considered without AI assistance. AI is not just helping customers shop within their existing brand preferences; it is actively expanding the set of brands customers consider.

What this means in practice. The brand consideration set has historically been determined by a combination of search visibility, paid advertising, and brand familiarity. Established brands enjoyed advantages because customers searched for known names, clicked familiar ads, and defaulted to brands they recognized. AI breaks this pattern. When a customer asks an AI to recommend, compare, or evaluate options, the AI surfaces alternatives based on relevance to the query, not based on brand familiarity to the customer. Smaller brands with strong product positioning surface alongside category leaders; new entrants get consideration that traditional discovery channels would not have produced; private-label and direct-to-consumer brands appear in consideration sets they wouldn’t have entered through search.

Why this matters strategically. Established brands lose part of their structural advantage. Newer brands gain access to consideration they couldn’t have purchased through paid channels. The competitive landscape shifts toward brands with strong product fundamentals (verifiable claims, structured product data, credible reviews, consistent positioning) and away from brands with primarily marketing-driven advantages. For CMOs, the brand strategy implications are concrete: brand authority increasingly depends on what AI can verify about the brand from public information, not on what the brand can spend to be seen. For category leaders, this is a defensive challenge; for challenger brands, it is the largest competitive opportunity in retail in years.

Shift 3: AI Drives Larger Baskets

The finding. 37% of AI-assisted shoppers in the Q2 2026 Locus survey report buying more items in a single order when using AI compared to their typical shopping behavior. AI is functioning as a measurable upsell and cross-sell engine in mainstream consumer shopping.

What this means in practice. AI-assisted shoppers receive contextual recommendations that human shoppers would not typically encounter at the same depth. “What goes with this?” produces complementary product suggestions; “What else might I need?” surfaces accessory and replenishment options; “How can I save on shipping?” reveals basket-size thresholds for free shipping; “Are there bundle options?” surfaces multi-product configurations. The AI conversation produces basket-building patterns that retailer-side recommendation engines have been trying to replicate for years, but with the trust signal of AI-summarized analysis rather than retailer-sponsored placement.

45% of US online shoppers in the Q2 2026 Locus survey report using AI tools as part of their shopping journey, either as primary or secondary tools.

Why this matters strategically. The unit economics of AI-assisted shopping differ from search-driven shopping. Average order value rises when customers consolidate purchases that would otherwise have happened across multiple visits. Customer acquisition cost amortizes across larger orders. Fulfillment economics improve when basket size grows because shipping costs amortize across more items. But operational complexity increases too: larger baskets mean more SKUs per order, more packing complexity, more potential for partial-stock issues, more sensitivity to delivery date promises across the multi-item order. The 37% finding is operationally significant because it changes the cart-to-fulfillment economics that retailers planned operations around.

What This Means for Retail and E-Commerce Executives

The three behavioral shifts compound across the retail organization, with implications that cut across function:

For CMOs and Heads of Marketing. Brand consideration is being reshuffled by AI rather than determined primarily by paid search and brand familiarity. Marketing strategies need to address how brands surface in AI-mediated discovery, what claims AI can verify about the brand, and how product information is structured for AI consumption rather than purely for human reading.

For Heads of E-Commerce and Digital. Checkout, cart, and product detail page architectures designed for search-engine shoppers need to evolve for AI-assisted shoppers. Structured product data (schema markup, accurate inventory signals, transparent shipping commitments) becomes more important than visual merchandising designed for human scrolling.

For COOs and Heads of Operations. Larger basket sizes change fulfillment economics. More multi-item orders need to be planned for, packed efficiently, and delivered against promises that the cart made at the AI-assisted purchase moment. Customer service teams need to serve a shopper who arrives with AI-summarized expectations rather than retailer-set expectations.

For CFOs and CEOs. The 45% finding is balance-sheet relevant. Customer acquisition economics, marketing ROI, fulfillment cost structure, and competitive positioning are all affected by the AI shopping shift. The strategic question is not whether to plan for the AI shopper; it is how quickly the organization can recalibrate.

The Q2 2026 survey makes clear that the AI shopper is the mainstream shopper. The strategic question for retail and e-commerce executives is whether the operation is planning around the customer it had in 2025, or the customer it will actually meet in the remainder of 2026.

FAQs

How are US shoppers using AI for shopping in 2026?

According to Locus’s Q2 2026 US Consumer Survey of 1,000+ active US online shoppers, 45% now use AI tools like ChatGPT and Claude as part of their shopping journey. Customers use AI for product discovery, brand comparison, review summarization, value evaluation, and purchase decisions. The AI-assisted shopper navigates a different journey than the search-driven shopper of previous years, with implications across marketing, e-commerce, operations, and customer experience.

What percentage of US shoppers use AI for shopping?

Locus’s Q2 2026 US Consumer Survey of 1,000+ US online shoppers found that 45% use AI tools for shopping, either as primary or secondary tools. The 45% figure crosses a mainstream adoption threshold, meaning AI shopping is no longer the behavior of early adopters but of mainstream consumers. The finding has direct implications for marketing strategy, e-commerce architecture, and operational planning at US retailers.

Does AI shopping change brand consideration?

Yes. The Q2 2026 Locus survey found that 39% of AI-assisted shoppers are more likely to try new brands they wouldn’t have considered without AI. AI is expanding brand consideration sets beyond what search visibility and brand familiarity have historically determined. Smaller brands with strong product fundamentals gain consideration alongside category leaders; established brands lose part of their structural advantage. For CMOs, this is a meaningful competitive shift requiring brand strategy recalibration.

Does AI shopping increase order size?

Yes. The Q2 2026 Locus survey found that 37% of AI-assisted shoppers buy more items in a single order when using AI compared to their typical shopping behavior. AI functions as a measurable upsell and cross-sell engine through contextual recommendations, basket-size threshold suggestions, and bundle configurations. The basket-size shift has direct implications for unit economics, fulfillment operations, and shipping cost amortization at the operational level.

What should retailers do about AI-assisted shopping?

The Q2 2026 Locus survey findings suggest retail and e-commerce executives should address the shift across four cross-functional dimensions. Marketing strategies need to address AI-mediated discovery and brand verification. E-commerce architectures need to evolve from search-shopper-optimized to AI-shopper-optimized (structured product data, accurate inventory signals, transparent shipping commitments). Operations need to handle larger basket sizes and AI-set customer expectations. Customer experience teams need to serve a shopper who arrives with different journey context. The compound shift requires organizational planning, not isolated channel adjustments.

How was Locus’s Q2 2026 US Consumer Survey conducted?

Locus’s Q2 2026 US Consumer Survey was conducted with 1,000+ active US online shoppers and covers behavior change across discovery, purchase, fulfillment, and post-purchase experience. The survey includes findings on AI-assisted shopping behavior, delivery and returns preferences, refund-speed loyalty patterns, generational differences in shopping behavior, and brand-trial patterns. The full survey findings are available in Locus’s Q2 2026 report.