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Luckin Coffee AI Scheduling Draws Barista Complaints Over Workload

March 19, 2025
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How Does Luckin Coffee AI Scheduling Affect Baristas?

Luckin Coffee introduced an internal AI scheduling system that uses historical business data to predict daily staffing and working hours per store. Employees say the system relies mainly on hourly cup output as its core reference. That approach, they argue, ignores cleaning, ingredient preparation, and shelf-life checks, leaving baristas working alone and sometimes doing unpaid overtime.

Under the new rules, if the AI judges a store's cup output as low, it schedules only one person on duty to cut labor cost. Staff report that eating, drinking water, and bathroom breaks become difficult, and some describe feeling like a machine behind the bar. The dispute highlights how algorithm-driven efficiency can overlook the invisible work that barista coffee origin and daily service depend on.

Luckin Coffee recently launched an internal AI-based store scheduling system that collects historical business data to predict the daily staffing and working hours needed at each store, in an attempt to allocate existing manpower more efficiently. However, this seemingly scientific automated scheduling has drawn a flood of complaints from Luckin employees. They point out that the system uses hourly cup output as its sole core reference, completely ignoring a large amount of invisible work such as cleaning, ingredient preparation, and shelf-life checks, leaving baristas working alone run ragged and even forced to work unpaid overtime just to finish up. Some employees say outright that they feel like a machine that never stops running behind the bar, with even eating, drinking water, and going to the bathroom becoming a luxury. This algorithm-driven efficiency reform is pushing frontline baristas to the brink of physical and mental exhaustion.

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Recently, Luckin Coffee upgraded its internal store employee scheduling and working-hours system, introducing AI technology to aggregate multiple sets of data from stores' past operating periods, and based on this to calculate the daily staffing numbers and corresponding working hours for each store, hoping to deploy existing manpower in a more efficient and reasonable way.

However, this brand-new scheduling method has drawn a large number of complaints from Luckin store employees, many of whom have taken to social platforms to post about the torment that automated scheduling has brought them.

According to Luckin employees, the new scheduling system's most core reference is the number of products sold by the store. The system uses historical data to predict the number of products for a certain time period the next day, and then arranges corresponding staffing based on that prediction. Simply put, the system first estimates the store's cup output; if the AI judges that a store has low cup output and sluggish business, it schedules only one person on duty, thereby driving down the labor cost required by each store.

At first listen, this seems not much different from the past scheduling system, but many employees say outright that this new set of operating rules only looks at hourly cup output to determine staffing, without taking into account the hard-to-see work that on-duty staff must also handle besides making drinks, such as cleaning, inventory counting, ingredient preparation, and shelf-life checks.

As a result, most people say that the actual workload they need to complete during their shift far exceeds the AI's estimate, and sometimes, because they cannot finish within the prescribed time, they can only work unpaid overtime for half an hour or even an hour to catch up on unfinished tasks.

But once a store suddenly receives a large order, or a newly introduced tea-extraction machine suddenly "goes on strike," or the cream charger happens to run out, and other such situations arise, the employee watching the store alone seems to enter a hell-difficulty work mode—having to produce drinks at high speed to ensure the store's on-time rate, while also completing various cleaning tasks assigned by the back office, keeping the bar clean and tidy, and still maintaining politeness and soothing customers' emotions when they urge their orders.

Some employees, finding humor in their misery, joke that even Nezha with three heads and six arms would probably work himself smoking hot trying to meet Luckin's demands of "want this, want that, and want more." "Like a perpetual motion machine, spinning nonstop," "Who on earth came up with this crappy scheduling, treating employees like beast-of-burden fighter jets," "Already on the road to being driven crazy and forced to resign," "Now not caring whether workers live or die has become a trend," "Luckin simply doesn't care whether people need to eat, drink water, or go to the bathroom."

Luckin's use of AI automatic scheduling causes employee dissatisfaction, cup output algorithm accused of ignoring invisible workload

They say that on the surface, the system scheduling gives employees a reasonable working duration and appears to allocate each store's human resources appropriately, but the actual situation is completely different. Their real working hours are utterly different from what the system arranges, and a lone employee on duty during peak hours simply cannot get an extra person to help handle the orders endlessly spitting out of the receipt printer, and can only become a robot that never stops behind the bar, numbly completing one receipt after another.

These various experiences have prompted many employees to loudly call for the management personnel who came up with new tricks like on-time rates and system scheduling to personally go to the stores and experience their miserable daily work, to feel the exhaustion and breakdown of employees who are so busy under Luckin's various rules that they cannot even eat, drink water, or go to the bathroom.

Image source: Xiaohongshu

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Luckin's use of AI automatic scheduling causes employee dissatisfaction, cup output algorithm accused of ignoring invisible workload

The above content is compiled by CoffeeHunters, a coffee news website.

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