Gary Black backs Uber over Tesla and Waymo for robotaxis at scale

An investor known for making pointed bets on mobility technology says the strongest odds of getting robotaxis from pilot projects to mass adoption belong to ride-hailing leader Uber Technologies Inc., not Elon Musk’s Tesla Inc. and not Alphabet Inc.’s Waymo.

In a recent interview posted by Yahoo Finance, Gary Black of The Future Fund LLC argued that Uber, with its large-scale consumer service and operations, is better positioned to execute the unglamorous work required for autonomous fleets to become a daily habit for millions of riders. Black’s core contention is that the market will reward companies that can turn technology into a working, repeatable transportation product, not just demonstrate autonomy in limited environments.

Black’s comparison grouped the major robotaxi approaches into competing bets on who can commercialize self-driving driving at the lowest friction. He put Uber’s existing marketplace at the center of his case, contrasting it with Tesla and Waymo. The comments, as reported, did not lay out a detailed technical scorecard or a timeline for when robotaxi services would become widely available.

Tesla, in this framing, is positioned less as the company that will run the first large autonomous taxi network, and more as a competitor with a different go-to-market and product pathway. Waymo is described as another contender in the same category, but Black’s view is that it is not the best shot to reach the broadest, most price-and-convenience-sensitive customers.

For Uber, Black’s argument highlights a structural advantage that matters even when autonomy works on paper: fleet operations. Robotaxi rollouts require reliable pickup, high uptime, regulatory navigation, rider trust, and the ability to scale demand while maintaining service quality. Ride-hailing incumbents also hold data about routes, pickup patterns, and real-world customer expectations, which can influence how quickly an autonomous service can be optimized for the routes and situations riders actually use.

The broader debate in robotaxis has increasingly turned from “can it drive” to “can it operate profitably and safely as a service.” That shifts attention toward companies that already have rider acquisition channels, dispatch systems, customer support infrastructure, and the ability to iterate daily based on observed performance.

Still, the Yahoo Finance piece, based on its published framing, provides limited detail on the specific assumptions behind Black’s call. It does not include the granular evidence one would normally expect in a quantified forecast, such as unit economics, fleet utilization targets, accident or safety metrics, or regulatory milestones tied to a particular city rollout. Those particulars are essential for evaluating how the conclusion could change if costs, approval timelines, or performance differ from expectations.

What to watch next is whether Uber expands or accelerates autonomous-ride initiatives and whether Tesla and Waymo respond with concrete commercialization steps that address the operational constraints that ride-hailing incumbents may already have partially solved. In the meantime, Black’s comments underscore that in robotaxis, investor confidence may hinge as much on execution capacity and scale as on autonomy itself.