‘The thought behind it was great, but the execution was proving difficult': Starbucks abandons AI inventory tool after only nine months following multiple errors — coffee giant says it needs to 'focus on consistency and execution at scale' | Tech Radar

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‘The thought behind it was great, but the execution was proving difficult': Starbucks abandons AI inventory tool after only nine months following multiple errors — coffee giant says it needs to 'focus on consistency and execution at scale'

Starbucks abandons problematic AI inventory tool – manual checks return

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Starbucks pulls AI inventory tool after nine months due to real-world challenges

The AI failed to recognize or distinguish between stock items, forcing manual intervention

Other AI and tech improvements continue to roll out under ‘Back to Starbucks’ transformation

Starbucks has officially ended its highly publicized ‘Automated Counting’ AI inventory program across all of its North American stores just nine months after it was launched in September 2025.

Developed alongside Seattle-based computer vision firm Nomad Go, the app was designed to use on-device 3D spatial intelligence, computer vision, augmented reality and Li DAR sensors to give stores real-time visibility into stock shortages.

CEO Brian Niccol had hoped that the tool would free up baristas from non-productive administrative work to deliver more to customers, however reports indicate the technology ultimately failed to revolutionize store admin.

Failed Starbucks AI system gets pulled just months after launch

“Our goal is simple - if it's on the menu, customers should be able to order it,” Starbucks said (via Reuters), justifying the tech’s place in its stores.

In early 2026, the global coffee chain announced its ‘Back to Starbucks’ transformation plan, targeting revenue growth, more comparable store sales and over 2,000 net new stores globally (including around 400 in the US).

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The problems came when the tech was deployed and tested at scale, because stores found that the computer vision model struggled with basic spatial awareness and object recognition, frequently overcounting items, overlooking stock or mislabeling products.

Most notably, the tool was unable to differentiate between similar items, like whole, oat and almost milk cartons. Starbucks also inadvertently showed the app completely missing a syrup bottle in a promotional video.

In the end, workers complained about having to force the AI to read shelves by waving and angling tablets in specific ways to trigger sensors, making it slower than entering the details manually in the first place.

Starbucks has since deleted the associated blog posts praising the tool for its efficacy, marking a full 180 compared with early, positive narratives.

“Thanks for discontinuing Automatic Counting,” one worker wrote. “The thought behind it was great, but the execution was proving difficult.”

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The company has now returned to manual inventory checks, but remains committed to a renewed, high-frequency store replenishment model to prevent customers from being greeted with out-of-stock drinks.

Though Starbucks is in the limelight for this particular example, the issues primarily revolve around computer vision and artificial intelligence outside the realms of text. In unpredictable, tightly-packed retail stockrooms with obscured labels, lighting variations and other variables, automated systems are still overcome with major challenges.

Even though CEO Brian Niccol had previously introduced this efficiency scheme to fix chronic product shortages and long wait times, Starbucks announced a 9% increase in quarterly revenues in Q2 to $9.5 billion as well as a 7.1% rise in comparable store sales across North America.

“We have more work to do, but we're pleased to see the combination of our comp growth and cost discipline starting to show up in margins,” CFO Cathy Smith added.

Another tech improvement that doesn’t appear to have gone away with the stock check automation is Starbucks’ new Smart Queue system, introduced in the company’s earlier ‘Back to Starbucks’ plan. It’s designed to balance and prioritize incoming tickets across in-store, mobile, drive-through and delivery orders to ensure that customers get seen to promptly.

Looking ahead, though the inventory management tool failed, the company hasn’t removed mention of its AI plans, such as “leveraging artificial intelligence to support partners, including supply chain and scheduling tools.”

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With several years’ experience freelancing in tech and automotive circles, Craig’s specific interests lie in technology that is designed to better our lives, including AI and ML, productivity aids, and smart fitness. He is also passionate about cars and the decarbonisation of personal transportation. As an avid bargain-hunter, you can be sure that any deal Craig finds is top value!

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