AI is Collapsing Decision Overhead in Grocery’s Hardest Orders
Platforms like Albertsons’ Celebrations show how complex purchases are being normalized
Some of the most profitable categories in grocery, like custom cakes, catering trays, and event-driven bundles, have remained stubbornly difficult to digitize. These orders require advance notice and coordination across multiple store divisions (think bakery, deli, floral, and general merchandise), each with its own inventory rules and fulfillment timelines.
As a result, they have long been handled through in-store conversations, phone calls, or fragmented online forms rather than standard e-commerce flows.
Recent retail AI deployments are targeting these failure points. Instead of focusing on browsing or content, retailers are applying AI to the mechanics that cause complex orders to break down. The aim is to remove the operational friction that prevents these purchases from being completed quickly and reliably online.
Albertsons Cos.’ new Celebrations platform offers an example of how that is being executed. Launched across the company’s banners, Celebrations consolidates custom cakes, floral, catering, décor, beverages, and related items into a single ordering experience.
Read more: Albertsons Wants AI Woven Into Every Part of the Grocery Business
“We’re enhancing the shopping experience for our customers by adding the capability to plan entire celebrations with the same ease as ordering their weekly groceries,” said Jill Pavlovich, senior vice president of digital customer experience at Albertsons Cos.
AI and the Collapse of Decision Overhead
What makes event-driven purchases difficult online is not their price or infrequency, but the number of decisions they impose. Customers must estimate quantities, choose themes, ensure items work together, account for preparation times, and align pickup or delivery windows. Each step adds friction, and each unresolved dependency increases the likelihood that an order is delayed or abandoned.
In Celebrations, Albertsons uses its AI shopping assistant to manage those dependencies. The assistant, which rolled out across banners in late 2025, guides customers through planning tasks, assembles baskets across departments, and enforces constraints such as availability and lead times. The system does not automate choices on the customer’s behalf, but it removes the need for shoppers to coordinate each element manually.
That same assistant was introduced more broadly as a way to shorten the time required to complete online grocery orders, according to the company. In earlier coverage of the rollout, Albertsons said the tool could reduce the time spent building a digital cart from roughly 40-45 minutes to just a few minutes by handling tasks such as list creation, meal planning, and cart assembly.
“Our goal at Albertsons Companies is to make our customers’ lives easier, and by implementing AI-powered features across the customer journey from discovery to purchase, we are delivering an experience that’s faster, easier and more enjoyable,” Pavlovich said when discussing the AI assistant.
When Complex Purchases Become Repeatable Systems
A purchase does not need to be frequent to behave like a commodity. What matters is whether the process is repeatable and the outcome predictable. Research on service design has shown that even infrequent transactions can feel routine when variability is handled by the system rather than pushed onto the customer. Standardization, not volume, is what removes friction from complex interactions.
AI is being applied to manage variation that would otherwise interrupt the transaction. Custom messages, dietary requirements, uncertain headcounts, and mixed fulfillment windows introduce edge cases that traditional e-commerce systems struggle to accommodate. Research on enterprise AI adoption shows that these systems are most effective when used to manage exceptions and dependencies, rather than average cases, allowing transactions to continue even when conditions vary.
The economic effect of this design approach shows up in basket structure. When convenience improves and coordination costs drop, customers are more likely to purchase across categories in a single transaction. Reduced friction increases attachment rates and basket size by collapsing decisions that would otherwise be made separately.
Albertsons is not alone in applying AI to normalize complex shopping behavior. Other large retailers are pursuing similar strategies focused on completing entire baskets rather than optimizing item-by-item search. Walmart, for example, has positioned AI as a way to move beyond traditional search-based e-commerce toward systems that translate intent directly into completed orders. “For many years now, eCommerce shopping experiences have consisted of a search bar and a long list of item responses,” Walmart CEO Doug McMillon said. “That is about to change.”
Across these deployments, the common focus is operational. Analysts and industry researchers note that retail AI delivers the most value when it shortens time to checkout, reduces handoffs, and manages coordination that previously fell to the customer. The technology is being applied where execution, not assortment or content, is the limiting factor.
Celebrations is and example of that approach in practice. The platform applies an existing AI system to a workflow that historically required human assistance and customer patience, with the goal of making event planning behave more like a standard grocery transaction.