AI Doesn’t Just Increase Buying, It Increases Conviction: Three Findings from the Q2 2026 US Consumer Survey

Key Takeaways

• Locus’s Q2 2026 US Consumer Survey finds AI users behave materially differently from non-AI users across brand consideration, basket size, and buying confidence — large enough to change demand, fulfillment, and brand strategy.
• AI users are 2x+ more likely to try new brands (39% vs 18%) and put more items in carts (37% vs 17%), and 3x+ more likely to feel confident buying fewer items (34% vs 11%). Three behaviors at once.
• Retailers reading AI as a single amplification trend miss the shift. Retailers reading three behaviors — wider consideration, larger baskets, deliberation — find the signal reshaping demand patterns.
• Operational implications cascade. Demand planning may underestimate volatility. Last-mile package mix shifts. Brand defensibility erodes while returns patterns evolve.
• For CSCOs, CMOs, and Heads of Ecommerce, Demand Planning, and Last-Mile, the question is whether architecture reads AI as three patterns — or one trend missing the structural shift.

AI-assisted shopping has crossed the threshold from emerging behavior into material consumer pattern. Among US consumers who already use AI tools for shopping — recommendation engines, conversational shopping assistants, AI-powered search, generative product discovery — buying behavior diverges materially from the non-AI consumer baseline. The divergence is not subtle. Locus’s Q2 2026 US Consumer Survey finds AI users are more than twice as likely than non-AI users across multiple buying behaviors simultaneously — and the behaviors don’t all point in the same direction.

Finding 1: AI Users Are More Than Twice as Likely to Try New Brands

The data. 18% of all US consumers say they’re likely to try new brands or products in their next purchase cycle. Among consumers who use AI tools for shopping, the figure rises to 39% — more than 2x the baseline rate.

What it means. AI-assisted discovery widens the consideration set materially. Consumers using AI tools encounter brands they wouldn’t have considered through search-and-browse discovery patterns. The expanded consideration set affects brand defensibility for incumbents and creates a discovery window for challenger brands.

Operational implications cascade. Demand planning models trained on incumbent loyalty assumptions may understate volume shifts as consumers test new brands at higher rates.

Finding 2: AI Users Put More Than Twice the Items in Their Carts

The data. 17% of all US consumers say they buy more items per order than they did previously. Among AI users, the figure rises to 37% — also more than 2x.

What it means. AI assistants function as recommenders during the shopping flow, and the recommendations are landing. Consumers using AI tools add more items per order — bundled recommendations, complementary products, accessories, alternatives all surface during the AI-assisted shopping experience in ways that lift basket size.

Operational implications cascade. Demand planning needs basket composition awareness, not just volume forecasting. The same total order volume distributed across larger baskets produces different fulfillment economics than across more, smaller orders.

Finding 3: AI Users Are More Than Three Times More Confident Buying Fewer Items

The data. 11% of all US consumers say they feel confident buying fewer items than before. Among AI users, the figure rises to 34% — more than 3x.

What it means. AI isn’t only amplifying buying. Some consumers use AI tools to make more deliberate decisions, comparing options more rigorously, reaching higher confidence in fewer purchases.

Operational implications cascade. Returns patterns evolve as deliberate buying becomes more common — deliberate purchases typically return at lower rates than impulse purchases.

Three Behaviors at Once: The Architectural Reading

The three findings appear contradictory only if AI behavior is read as a single trend. Read as three behaviors happening simultaneously, the findings form a coherent picture: AI mediates more of the shopping experience, and the mediation can produce wider consideration, larger baskets, or more deliberate purchasing depending on what the shopper is using AI for.

Retailers reading AI behavior as a single amplification trend miss the structural shift. Demand planning calibrated to “AI makes consumers buy more” misses the deliberation pattern. Brand strategy assuming “AI commoditizes discovery” misses the conviction-building pattern.

FAQs

What did Locus’s Q2 2026 US Consumer Survey find about AI shopping behavior?

Locus’s Q2 2026 US Consumer Survey finds AI users behave materially differently from non-AI users across three connected dimensions. AI users are more than 2x more likely to try new brands (39% vs 18%), more than 2x more likely to put more items in their carts (37% vs 17%), and more than 3x more likely to feel confident buying fewer items (34% vs 11%).

How does AI change consumer brand consideration?

AI-assisted shopping widens the consideration set materially. Consumers using AI tools encounter brands they wouldn’t have found through traditional search-and-browse patterns. 39% of AI users say they’re likely to try new brands compared with 18% of all consumers — more than twice the baseline rate.

Why do AI users put more items in their carts?

AI assistants function as recommenders during shopping flows, and the recommendations are landing. Bundled recommendations, complementary products, accessories, and alternatives surface during AI-assisted shopping.

Why are some AI users buying fewer items?

Some consumers use AI for deliberation rather than amplification — comparing options more rigorously, reaching higher confidence in fewer purchases. 34% of AI users feel confident buying fewer items compared with 11% of all consumers.