How AI Shopping Assistants Are Changing Grocery Basket Size

Albertsons reported a 10% basket-size increase from its AI-powered "Ask AI" search. AWG's SmartMeals assistant is showing a 22% lift. Shoppers using smart carts spend 32% more, per Bayes Business School research. The pattern across every major grocery AI rollout in 2026 is the same: AI-assisted shopping produces measurably bigger baskets.

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The results, reported by the companies themselves

Albertsons: a 10% increase in basket size for customers using its "Ask AI" search capability, as reported in the company's January 2026 earnings call.

AWG (Associated Wholesale Grocers): SmartMeals, its AI shopping assistant powered by Breez AI, is showing a 22% lift in average basket size and a 72% increase in loyalty signups at participating stores — strong enough results that the tool moved from pilot to wide-scale deployment as of March 2026.

Cooklist: its AI shopping assistant is producing double-digit basket-size growth among shoppers who use it, with a rollout expansion in June 2026 planned across 10 additional grocery banners and roughly seven million more shoppers.

Instacart: reports that its agentic AI assistant produces orders that are generally larger than typical orders — evidence that shoppers who opt into the AI-assisted flow use it to support their full weekly shopping list, not just a single quick purchase.

Independent research: a Bayes Business School study found shoppers engaging with smart shopping carts spent 32% more on average than those who didn't, with the largest differences observed in the afternoons and on weekends.

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Why AI assistance specifically drives basket size, not just conversion

The mechanism across these examples is consistent: these tools aren't just making checkout faster, they're actively surfacing items the shopper would otherwise have to remember or search for individually — meal-planning-to-basket flows, recipe-based product pairings, and reorder suggestions all add items the shopper didn't specifically search for but recognizes as relevant once suggested. That's structurally different from a search-bar improvement, which mostly helps shoppers find what they were already looking for faster.

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What this means if you're not the retailer building the AI assistant

Every example above is a retailer's own first-party tool. If you're a CPG or DTC brand selling through these retailers, the basket-size lift isn't automatic for your specific products — it depends on whether your product data is structured well enough for the retailer's AI assistant to actually surface you as a relevant addition. A meal-planning AI recommending a recipe will suggest specific branded products only if those products' data (category, use case, pairing information) is complete and machine-readable in the retailer's system.

This is the same structured-data problem that determines AI shopping visibility everywhere else — see How to Optimize Your Product Catalog for AI Agents for the full checklist. A brand with excellent products and thin catalog data gets passed over by these assistants in favor of a competitor whose data is simply easier for the AI to work with.

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The open question worth tracking

Every example here is retailer-led — Albertsons, AWG, Cooklist, and Instacart are all building or licensing their own AI shopping layer. As more of grocery shopping moves through these first-party AI assistants, brand visibility inside them becomes a real, separate discipline from visibility on ChatGPT, Gemini, or Perplexity — a retailer's AI assistant draws from that retailer's own catalog and data feed, not the open web. If you sell through any of these channels, understanding how your specific data flows into that retailer's AI layer is worth investigating directly, not assumed.

Book a demo if you want help auditing whether your product data is actually visible and well-structured across the retail AI layers relevant to your category.

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