Uber’s latest move signals a sharp turn toward asset optimization in ride-hailing. The company announced on Friday it will deploy new AI-driven pricing and dispatch algorithms across its global fleet starting next quarter. These tools aim to reduce idle time for drivers by up to 23% and cut operational costs by 11%, according to internal documents reviewed by TechCrunch.
The initiative, codenamed Project Nimbus, integrates real-time traffic data with historical demand patterns. Uber’s chief product officer, Lior Ron, confirmed the changes in a briefing. He said the goal is to improve earnings for drivers while maintaining competitive fares for riders. The company has already tested the system in Los Angeles and Chicago, where average wait times dropped from 4.2 minutes to 2.8 minutes.
Industry analysts see this as Uber’s response to shrinking profit margins. Ride-hailing companies have faced pressure from rising insurance and vehicle costs. Uber’s stock dipped 3.4% after the announcement, though analysts at JPMorgan called the move "a necessary pivot."
The update also includes stricter vehicle performance standards. Drivers with cars older than six years or with poor maintenance records will receive lower dispatch priority. Uber will offer financing options to help drivers upgrade their vehicles.
Critics argue the changes could push out part-time drivers who cannot afford upgrades. A driver in San Francisco, who asked not to be named, said his earnings dropped 15% after the pilot program started. Uber has not yet addressed these concerns publicly.
Source: techcrunch.com