The chain is reverting to manual counts across North America, ending one of CEO Brian Niccol’s more visible technology bets and adding another data point to the file marked “enterprise AI pilots that did not survive contact with the real store.”
Starbucks has retired the AI-powered inventory tool it rolled out across its North American stores last September, according to an internal newsletter reviewed by Reuters and confirmed by the company.
“Starting today, Automated Counting will be retired,” the Monday memo read. “Beverage components and milk will now be counted the same way you count other inventory categories in your coffeehouse.” In other words, by hand.
The tool, built by Seattle-based NomadGo, used tablet-mounted cameras and LiDAR to scan shelves of syrups, milks and other beverage components and produce automatic counts, replacing manual stock-takes for selected categories.
It had been in development for several years and was expanded nationwide after Brian Niccol took over as chief executive in September 2024, as part of his “Back to Starbucks” turnaround.
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The problem, according to Reuters’ February reporting and the company’s own internal materials, was that the tool struggled with the everyday job of telling one white liquid from another.
The app frequently miscounted or mislabelled items, particularly similar-looking products such as oat milk and dairy. A promotional video Starbucks itself released at launch showed the system failing to register a bottle of peppermint syrup sitting on the shelf as it counted the bottles next to it, which is the kind of thing that tends to look worse in hindsight than at the time.
In a statement to Reuters on Thursday, Starbucks framed the move as a standardisation exercise rather than a retreat.
The decision came from “a decision to standardise how inventory is counted across coffeehouses as we continue to focus on consistency and execution at scale,” the company said, adding that it is moving toward more frequent daily replenishments and continued supply chain improvements.
An internal note shared by the company quoted an employee thanking the team for ending the programme: “The thought behind it was great, but the execution was proving difficult.”
The decision matters because inventory was supposed to be the easy bit. Four Starbucks CEOs over five years have blamed lost sales on the company’s struggle to keep stores reliably stocked. In early 2024, by the company’s own admission, fewer than a third of deliveries to Starbucks distribution centres arrived on time and in full.
Automated Counting was meant to give the chain the live store-level visibility it had been missing, and was one of Niccol’s headline operational fixes.
It also lands at a moment when the wider record on enterprise AI is starting to look less generous than the pitch decks. MIT’s NANDA initiative found last year that 95% of enterprise generative-AI pilots delivered no measurable impact on the P&L, despite roughly $30 to $40bn in spend, with only 5% reaching production.
The Starbucks tool was not generative AI, but the shape of the failure is familiar: a deeply integrated, store-level workflow proved harder to automate reliably than the demo suggested.
The financial backdrop is mixed enough that the decision will be read both ways. Starbucks posted its strongest quarterly sales growth in two and a half years last month, and the stock is up 24% so far in 2026, but operating margins in its core North American market have fallen to 9.9%, down from 18% two years earlier.
Niccol has continued to invest in other technology bets, including AI tools to sequence orders and assist baristas during peaks. NomadGo, for its part, told Reuters it is “continuously learning from customer and user feedback” to improve its products.
The next test is whether daily replenishments and manual counts can do what the algorithm could not, which is keep peppermint syrup on the shelf.
