Now Uber is putting artificial intelligence (AI) inside all of it.

The company introduced a driver-facing AI assistant that translates live marketplace data into positioning advice and a voice interface that lets riders book in natural speech. This isn’t a chatbot bolted onto an existing app. It is AI embedded in a logistics network where millions of routing decisions, payments and deliveries happen at the same time.

No Two Cities Run the Same

A driver in Lagos asking whether the airport run pays gets a different answer than one in São Paulo, because the system pulls live marketplace data for that city at that moment. According to OpenAI, which operates the AI, the assistant cuts new-driver ramp-up time, compressing what previously took hundreds of trips to learn. Uber onboards drivers across dozens of languages and regulatory environments.

“We want to enable drivers to make better decisions for themselves by providing a summarized view of the marketplace and real-time insights,” said Dharmin Parikh, director of product management at Uber.

The rider-facing feature uses OpenAI’s Realtime API to handle complex spoken requests, such as a five-luggage airport pickup or a saved-location ride. Uber positioned voice as an accessibility tool for older and visually impaired riders, as well as a hands-free interface for drivers.

To keep the system reliable at scale, Uber built AI Guard, an internal layer that checks prompts and responses for safety, privacy and policy compliance and works to reduce factual errors. Drivers who get useful recommendations return to the assistant, ask more questions and log more productive time on the platform. “If users don’t trust the system, you lose them quickly,” Parikh said.

AI Adoption

Uber’s AI footprint runs deeper than the driver app. AI agents now write roughly 11% of live updates to Uber’s back-end systems, up from a fraction of a percent three months ago. That infrastructure manages pricing, matching logic and product features across every market Uber operates in.

Uber’s CTO Praveen Neppalli Naga told The Information that AI spending had blown past every projection the company made, a consequence of token-based pricing that scales directly with use. According to PYMNTS, AI tools don’t carry fixed post-deployment costs the way traditional software does. They scale with demand. At Uber’s volumes, demand moves fast.

The multi-agent routing model directs simpler queries to cheaper models and reserves larger ones for tasks that require heavier reasoning. It functions as a cost-management structure as much as a technical one.

Uber’s Q1 2026 results showed a company that has moved its frame from ride volume to platform infrastructure, PYMNTS reported. Uber is building itself into a mobility and commerce platform, adding AI tools, delivery, travel booking and autonomous vehicle infrastructure across its network.

Uber now runs the driver assistant and voice booking feature in beta mode for U.S. users. The company said a broader rollout is set to arrive in the coming weeks.