Uber Cuts 23% of HR Staff, but Says AI Has Nothing to Do with It

Uber downsizes its "People and Places" division with a significant cut. The company led by Dara Khosrowshahi has announced the layoffs of nearly a quarter of its staff dedicated to human resources and recruitment. This targeted approach, according to official spokespersons, amounts to less than 1% of Uber's global workforce, currently estimated at around 34,000 employees.

The move comes just a few weeks after the appointment of Jill Hazelbaker to the newly created role of Chief Corporate Affairs Officer and President. It was Hazelbaker, a cornerstone of the company since 2015, who clarified the details of the operation through an internal communication to employees. The official reason lies in the need to simplify teams deemed "too complex and fragmented," characterized by wide overlaps in responsibilities, unclear management of operational skills, and an excessive distance from the actual business needs and the commercial partners that should be supported on a daily basis.

Productivity and the Cost Issue of Artificial Intelligence
Despite the market witnessing a massive wave of layoffs in the technology sector, often directly justified by the adoption of automated systems, Uber has emphasized that this restructuring is not related to the introduction of generative algorithms. The necessity, reiterated by CEO Dara Khosrowshahi in a separate memo sent to staff, is focused on maximizing operational effectiveness of a department that has become structurally redundant during recent years of expansion.

However, the shadow of AI looms over the medium-term strategies of the ride-hailing giant. On one hand, Khosrowshahi confirmed that the pace of new hiring has undergone a physiological slowdown thanks to the productivity boost provided by the AI tools already in use; on the other hand, management is not convinced about the real financial returns.

Uber's Chief Operating Officer, Andrew Macdonald, raised a crucial issue for the company’s budgets, highlighting how the performance increase generated by AI is not yet directly proportional to the expenses incurred for the purchase and consumption of computational tokens. This misalignment demonstrates that the integration of generative artificial intelligence solutions still requires deep cost optimization before it can justify the direct replacement of human labor. In the meantime, Uber chooses the traditional restructuring route, focusing on regaining internal efficiency through streamlining workflows.