Uber sees leadership shakeup in AI data-labeling unit, with two senior executives departing

Uber is reportedly working through a wider leadership transition as it reorganizes parts of its artificial intelligence function, according to a report carried by Yahoo Finance.

The report, attributed to Bloomberg, says Uber’s senior director of engineering, Naga Kasu, recently left the company. It also says Pankaj Kamat, described as the director of product at Uber AI Solutions, has departed as well.

In addition to naming the two executives, the report characterizes the departures as dismissals tied to Uber’s AI work, specifically naming a data-labeling division. Data labeling is the process of attaching human-verified tags to raw data so machine-learning systems can learn from examples, a step that often sits between research and real-world deployment.

While the reported exits point to changes inside Uber’s AI organization, the post does not provide details on why the two leaders were removed, how their responsibilities will be reassigned, or whether the company plans additional staff changes beyond the pair mentioned.

Uber AI Solutions is the part of Uber’s business responsible for producing and supporting AI-driven capabilities, which typically require both model development and data operations. For many companies, the AI workflow includes building machine-learning models and preparing data at scale, including labeling and quality review, before models can be used in products and internal systems.

The shakeup also raises questions about how Uber is structuring accountability in AI, a function where engineering and product leaders often determine what gets built, how performance is measured, and how training pipelines are managed. Changes at the director level can announcement an attempt to align AI priorities with broader company goals, though neither the Yahoo Finance post nor the linked report included specifics on those goals.

Still, beyond naming the executives and the department they were associated with, no further information was disclosed in the material referenced in the article. There is no included timeline for the broader leadership transition, no explanation of any performance issues or restructuring rationale, and no confirmation from Uber about whether additional departures or reorgs are imminent.

For investors and industry watchers, the key item to monitor will be whether Uber publicly details AI organizational changes in upcoming interviews, earnings materials, or leadership announcements. The company’s disclosures around AI strategy, cost structure, and how it manages data operations could provide the clearest confirmation of what the leadership change is intended to accomplish.