Uber's Product Chief on AI Data, Robotaxis, and the Limits of the Super App
Uber CPO Sachin Kansal outlines a new AI data unit, a growing rivalry with Waymo, and why the company is expanding into travel and fintech without trying to be everything.
Uber is reshaping its business model, moving beyond rides and food delivery into travel, financial services, and AI data infrastructure. In a recent interview, Chief Product Officer Sachin Kansal laid out how the company plans to stay relevant as autonomous vehicles, new competitors, and platform consolidation pressure its core business from multiple directions.
AV Labs and the Data Hedge
The most consequential development Kansal discussed is the launch of AV Labs, a business unit that operates sensor-equipped vehicles to capture driving data. Uber frames this as support for its autonomous vehicle partners, but the strategic logic runs deeper. By building its own proprietary data layer, Uber gains leverage over companies like Waymo, which operate simultaneously as partners on the platform and as long-term competitors in the robotaxi market.
Drivers are also being brought into Uber's AI supply chain. The company now offers data-labeling tasks as an additional income stream, turning its existing driver network into a workforce that trains the machine learning models underpinning the platform. The play positions Uber as a data-as-a-service provider, one that stays central to the AI value chain regardless of which company ultimately wins the autonomous vehicle race.
Financial Services and the Membership Push
Kansal was direct about the super app question. Uber is not trying to mirror Asian platforms like Grab by becoming a full financial services provider. But the company is still moving in that direction, carefully. The Uber Pro card, a debit card giving drivers instant access to earnings, is being expanded. Similar financial tools are being tested for merchants in select global markets.
On the consumer side, Uber One, the company's membership program, now counts 51 million members. Kansal noted that membership is pulling mobility-only users into delivery and vice versa, building the kind of cross-platform stickiness that makes it harder for rivals like Lyft and DoorDash to poach users with discounts alone.
What This Means for Africa
Uber's pivot toward driver financial tools and data labeling carries real relevance for African markets. High vehicle financing costs, currency volatility, and limited access to formal credit make instant earnings and embedded financial services meaningful for drivers in cities like Lagos, Nairobi, and Accra. Local ride-hailing players, including Bolt, which has significant African market share, could find pressure building to match these offerings or risk losing drivers to platforms with deeper financial benefits.
The data labeling angle also matters. Companies like Samasource have demonstrated that African talent can be mobilized effectively for AI training work. If Uber scales its labeling program to African driver networks, it creates a new income layer for gig workers. But it also raises questions about data ownership. African cities are generating vast amounts of unique mobility data, from unstructured road networks to informal transit corridors, that do not map onto Western infrastructure assumptions. If local startups and governments do not move to capture and own that data, the autonomous vehicle solutions eventually deployed on African roads will be built on someone else's intelligence.
The company building the most useful map of how the world actually moves may end up with more power than the company operating the most vehicles.
Source: TechCrunch
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