Uber Technologies Inc. (NYSE: UBER) is exploring a plan to turn its millions of drivers into a distributed sensor network for autonomous vehicle developers, the company's technology chief said last week. "First we need to get the understanding of the sensor kits and how they all work," Chief Technology Officer Praveen Neppalli Naga reportedly said at TechCrunch's StrictlyVC event in San Francisco on April 30. "There are some regulations - we have to make sure every state has clarity on what sensors mean, and what sharing it means."
From Ride-Hailing To Data Infrastructure
Uber is currently piloting this approach through its AV Labs program. The initiative uses a modest fleet of company-operated, sensor-equipped vehicles that operate independently of Uber's main driver platform, TechCrunch reported.
The long-term ambition is far larger. Naga outlined plans at the TechCrunch event to eventually equip its millions of drivers' vehicles with sensors, which could create one of the largest real-world data collection platforms for autonomous vehicle companies.
Data Emerges As The Key Constraint
"The bottleneck is data," he said.
Naga said at TechCrunch's StrictlyVC event that the challenge in autonomous driving has shifted toward data availability, with companies needing highly specific, real-world scenarios to train their systems.
"You may be able to say, 'At this school intersection, I want some data at this time of day so I can train my models,'" he said. "The problem for all these companies is access to that data, because they don't have the capital to deploy the cars and go collect all this information."
Uber's Second Act In Autonomy
After selling its self-driving unit in 2020, Uber has shifted from building autonomous vehicles to supporting the companies that do, TechCrunch reported, adding that co-founder Travis Kalanick has called the exit a mistake.
Uber now works with more than 25 AV partners, including London-based Wayve, and is building what it calls an "AV cloud," a platform that provides labeled sensor data for model training.
Partners can also run algorithms in "shadow mode" during live Uber trips, allowing them to test performance without deploying vehicles.
Platform Power And Investment Strategy
Uber is also planning to increase direct investments in select AV partners, combining its role as marketplace operator with that of a data provider as the company expands partnerships across the autonomous vehicle ecosystem, the Financial Times reported in April.
Many AV developers already rely on Uber's platform for rider demand, giving the company leverage as it steps back from building vehicles itself. Recent partnerships, including additions to its fleet such as Amazon's Zoox, highlight that growing role.
Naga said scaling a sensor network across independent drivers will require navigating a patchwork of state-level regulations and that regulatory clarity will be essential before broader deployment.
Uber As A Core Data Layer
If successful, Uber could evolve into a core data layer for the autonomous industry, opening new revenue streams beyond ride-hailing.
That positioning comes as executives and industry observers increasingly point to cost and scaling challenges as key constraints on AV adoption, suggesting companies that can provide infrastructure and data at scale may hold an advantage.
As artificial intelligence expands beyond chatbots into real-world infrastructure and automation, some investors are also watching emerging companies focused on the future of work - including spatial computing and immersive productivity platforms.