Uber cuts middle management; AI isn't the first target

When a company reaches a certain stage, it's like a city road network during rush hour. There are enough cars and traffic lights, but the problem is too many command booths in between. According to Bloomberg's report, Uber plans to cut approximately 3,300 jobs, accounting for 10% of its global workforce, focusing on reducing management layers and reallocating resources. It sounds like another big tech diet, but I care more about why they aimed the knife at "management," starting with management layers.

From the data, there were signs. Bloomberg reported back in July that Uber cut about 10% of Community Operations staff, merged teams, eliminated management positions, and increased AI usage. In June, news emerged that the People division was cut by 23%, covering HR, recruiting, office facilities, and culture. Connecting these dots, AI is first compressing those who "make decisions for the frontline"; the frontline drivers haven't been directly replaced by it yet.

This actually fits the cost structure of platform companies well. Early on, fighting for market share meant hiring people to buy trust insurance. Drivers, passengers, merchants, regulators, public opinion—every link needed someone watching. Middle managers were human routers, responsible for breaking down goals, pushing progress, and handling exceptions. Later, as business stabilized, AI tools started taking over repetitive judgments, thinning the value of the router.

I recently used WorkBuddy for scheduling and asset organization, tweaking prompt engineering for a while. The more I used it, the more I felt that the bulk of savings from the model came from small actions like "glance at a sheet, ask about progress, pull a meeting to confirm," while writing emails was just a minor part. But once it hit temporary shift changes, supplier price revisions, or customer emotional explosions, it still stopped at the door. In other words, AI can compress coordination, but taking over responsibility is far off.

So the key in Uber's current adjustment is replacing organizational redundancy with processes, data, and automation; model strength and wage savings are just surface phenomena. Salesforce has similar signals: support teams dropped from 9,000 to 5,000 people, and the CEO even said Agentforce means the company doesn't need as many support heads. Put these two things together, and the industry vibe emerges. AI is first targeting the "interpretation layer" sandwiched between the frontline and upper management; the dirtiest, hardest frontline work is ranked later.

This round of layoffs looks more like platform companies admitting that buying trust with headcount and stability with middle management is no longer worth the money. Over the next year and a half, I expect to see more companies replicating this path: first cutting management roles in HR, customer service ops, and shared service centers, then redoing approval flows and task distribution. What will differentiate winners is who can transform the organization from "people managing people" to "task routing," rewriting exception handling, risk responsibility, and cost accounting into the system.

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📌 This article is compiled from Bloomberg Tech. Original text: https://www.bloomberg.com/news/articles/2026-09-02/uber-to-cut-3-300-jobs-in-company-overhaul-to-reduce-management-layers

Copyright belongs to the original author. This is a compilation and independent analysis based on public reports.