Uber uses OpenAI to help people earn smarter and book faster

Uber uses OpenAI to help people earn smarter and book faster Uber uses OpenAI to power AI assistants and voice features that help drivers earn smarter and riders book faster across a global real-time marketplace. Every day, millions of people rely on Uber to book rides, order meals, send packages, and earn flexibly. Behind every tap is a complex real-time marketplace shaped by traffic, weather, airport arrivals, local events, and demand. Uber operates at massive scale: 40 million trips per day, 10 million drivers and couriers across 15,000 cities in over 70 countries. Each city has its own operating dynamics, regulations, and rider behavior, creating a system that must adapt continuously at global scale. Uber has long used machine learning to support its marketplace. And now, with the benefit of large language models and OpenAI frontier models, Uber can reason across complex signals more quickly, deliver fast conversational responses, and power voice experiences inside the app. The collaboration between Uber and OpenAI is helping Uber build AI-powered products that simplify earning opportunities for drivers and couriers and reduce friction for riders. And using OpenAI’s models, Uber can ship streamlined products and experiences faster than ever. “For the first time, technology is leading what can be solved. Problems that once felt out of reach are now possible to address.” For drivers, flexibility is one of Uber’s biggest strengths. Some drive full-time, others just on weekends, while some drive between classes or shifts. This flexibility also means drivers are constantly evaluating options and asking questions: Where should I position myself right now? Is the airport worth driving to? Should I switch from rides to deliveries during lunch? Why did my earnings look different today? To help answer those questions, Uber developed Uber Assistant, an AI-powered assistant designed to help drivers throughout their lifecycle on the platform—from onboarding and first trips to day-to-day earnings optimization. “We want to enable drivers to make better decisions for themselves by providing a summarized view of the marketplace and real-time insights,” says Dharmin Parikh, Director of Product Management at Uber. The Assistant helps drivers where and when to earn by turning complex data like earnings trends and heatmaps into simple, actionable positioning insights. They can then ask follow-up questions in plain language and receive tailored responses and easily navigate the app. Uber’s goal is to reduce cognitive overhead—the effort required to interpret complex marketplace data while trying to earn. That has proven especially valuable for new drivers. Uber found that using AI to summarize and easily communicate Uber’s real-world data can accelerate ramp-up by helping drivers learn workflows and marketplace dynamics much faster than through trial and error alone. While Uber Assistant was initially expected to help newer drivers most, experienced drivers also returned repeatedly to ask follow-up questions and optimize their time on the platform—validating the product as a long-term utility, not just an onboarding tool. “The Assistant is helping drivers ramp up quickly, compared to taking several hundreds of trips to understand how the platform…