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Uber commits $10B to hit 2,000 robotaxis by end of 2027

700 driverless vehicles expected on Uber's platform by December 31, 2026, scaling past 2,000 by end of 2027.

Uber disclosed specific fleet targets and a $10 billion capital commitment for autonomous vehicles in its third-quarter 2026 earnings release on November 4, setting what amounts to the company's first concrete driverless timeline1,2.

The company expects approximately 700 fully driverless vehicles on its platform by December 31, 2026, projecting that figure will climb past 2,000 by the close of 2027 and into the tens of thousands by 2028. Uber said it plans to spend $10 billion to reach the 2,000-vehicle mark. Around half of those robotaxis will serve the United States market, with the remainder split between Europe, Asia, and the Middle East across 20 cities.

"Our autonomous strategy is entering an important new phase as more of our partners move from development and testing into driverless commercial service," CEO Dara Khosrowshahi said in written remarks shared alongside the earnings release.

Uber's autonomous vehicle partner count now exceeds 25 developers, spanning technology companies, automakers, and AI software providers. Named partners include Waymo, a subsidiary of Alphabet Inc., Zoox (owned by Amazon), Wayve, Baidu, Rivian, Nvidia Corp., May Mobility, Momenta, and Motional.

Yet even if Uber hits its 2,000-vehicle target, it will trail Waymo, which already operates a fleet of around 4,000 cars across 15 U.S. cities. Waymo aims to double that count to 8,000 by the end of 2026 and reach 20,000 vehicles by the close of 2027[2]. And the relationship between the two companies is shifting: Waymo plans to end its exclusivity deal with Uber in Austin and Atlanta in January 2028, moving to offer rides directly through its own app in those markets[2].

ANALYSIS Uber's platform model — aggregating more than 25 AV developers rather than building its own stack — lets it post large committed-vehicle numbers quickly, but the per-city fleet density that determines rider wait times and unit economics remains dependent on partners whose own timelines are unproven at scale.

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