Retail AI can start with the team’s priority list

A specific task before a broad promise

In June 2025, Walmart announced an AI tool that recommends and prioritizes tasks, initially for overnight stocking. At the time of that announcement, use on other shifts was still being piloted. The company describes it as part of its associate app, providing guidance on where to focus work. The source does not detail its algorithm or establish that it is an autonomous agent.

The example shows an application beyond customer service. It addresses an internal question familiar to anyone running a store: what needs to happen now, and who can do it? That question can guide a smaller test without replicating Walmart’s infrastructure.

A priority needs a reason

An ordered list only helps if the team understands the criteria. Restocking a popular item may be urgent, but perhaps the delivery has not arrived. An overdue order may require contacting the customer before moving any goods. The right sequence depends on the day’s conditions, not just the task’s name.

Before introducing AI, describe the decisions the manager already makes. What usually comes first? Which constraints change the order? What information does the manager look for? Some of this knowledge can become explicit rules. Other parts require context and judgment, especially when new situations arise.

A first test that fits the routine

Choose one shift, one team and a set of open tasks. An initial workflow could gather records, flag missing information and prepare proposed priorities. Each suggestion would need to explain its reason and identify the underlying information. The manager would review the sequence before assigning work, with the ability to correct, postpone or reject a task.

The conversation with the manager is part of the design from the start. If the team already has a clear list and the real problem is understaffing, reorganizing it with AI may not remove the bottleneck. The initial assessment needs to distinguish those situations.

What must not get lost along the way

Gathering tasks requires an identifier, an owner and an understandable status. Open, awaiting delivery and complete mean different things. It also matters when information was updated: a recommendation based on yesterday’s inventory may create unnecessary work today. The team needs a straightforward way to correct the record.

Decide where the guidance will appear and how someone confirms completion. A dashboard that nobody checks creates another obligation. The workflow might need to use a tool the team already follows. That depends on access, integration and actual working habits, all of which need to be checked before implementation.

Assess usefulness, including when suggestions change

During the test, observe the time spent preparing the list, the manager’s changes and tasks reopened because of incorrect information. Ask whether the next step became easier to understand. Saving planning time is less valuable if the shift then follows unsuitable priorities or has to correct more mistakes afterward.

Do not treat every human change as a failure. A review may reveal information that never reached the system or a rule that was previously implicit. Record the reason, adjust the process and compare again. Ongoing review is a way to learn from the operation using criteria everyone can discuss.

What a smaller business can take from the case

The opportunity is to make everyday guidance clearer and easier to check. Start with a recurring situation, accessible information and a manager willing to review the output. Establish your own starting point and compare the work before and after. Your first test should answer its own question: can the team choose and carry out the next piece of work more effectively?