Uber wants to turn its sprawling driver network into something far bigger than a ride-hailing workforce: a living sensor grid for self-driving companies.

That plan surfaced Thursday night in San Francisco, where Uber chief technology officer Praveen Neppalli Naga described the idea during an interview at TechCrunch's StrictlyVC event. He framed it as a natural next step for AV Labs, a still-young program Uber announced in late January. The concept points to a simple but powerful strategy: use millions of vehicles already on the road to capture the kind of street-level information autonomous systems need to improve.

For Uber, the pitch carries obvious appeal. Building autonomous technology demands huge amounts of real-world data, and collecting it through dedicated fleets costs time and money. Uber already operates at global scale, with drivers moving through cities, suburbs, and edge cases that fixed test routes can miss. If the company can organize that flow into usable inputs for self-driving partners, it could carve out a new role in the race to commercialize autonomy without shouldering the full burden of building the vehicles itself.

Uber's latest autonomous push suggests the company sees its driver network not as a bridge to the future, but as the infrastructure that may help build it.

Key Facts

  • Uber's CTO outlined the sensor-grid idea at TechCrunch's StrictlyVC event in San Francisco.
  • The company links the plan to AV Labs, a program it announced in late January.
  • The strategy would use Uber's large driver base to gather road-level data for self-driving companies.
  • Reports indicate Uber aims to expand its role in autonomous technology through partnerships and data infrastructure.

The idea also sharpens a tension inside the autonomous transition. Uber relies on human drivers today, yet it now appears eager to position those same drivers as part of the machinery that could accelerate driverless systems tomorrow. That does not mean an immediate replacement is at hand, and the company has not laid out detailed operating mechanics in the information available so far. But the direction is clear: Uber wants to monetize its network not just through trips, but through information.

What comes next will matter well beyond Uber. Self-driving developers need richer, broader, and more current data to train and validate their systems, while platform companies want a durable place in that value chain. If Uber can turn everyday trips into a scalable data pipeline, it may gain leverage in the autonomous economy even before robotaxis reach mass adoption. The next test will center on execution: how Uber structures the program, what partners sign on, and whether this data-first strategy gives the company a stronger hand in the future of transportation.