Uber's AI Solutions data-labeling arm is using Indian drivers, offering extra income for completing micro tasks in the Uber app, like tagging objects in photos
Pranav Mukul / The Economic Times :
Context & Ripple Effects
Uber's AI Solutions effort builds on its 2024 launch of Scaled Solutions, which recruited gig workers across several countries for data-labeling work. This report shows the service being embedded in an existing driver workflow in India rather than operating solely as a separate labor marketplace.
The move also extends Uber's use of its app network beyond transport and delivery: Uber Eats has already used AI features and paid some customers to contribute food photos, linking platform participation to AI-data production.
First-order effects
- Indian drivers can access small labeling jobs alongside driving through the Uber app, creating an additional, task-based earnings channel.
- Uber gains a directly managed pool of workers for image-tagging tasks through AI Solutions, using its existing app and driver relationship.
Second-order effects
- Uber can test whether in-app task offers improve driver engagement without relying entirely on ride demand; task availability and pay will determine whether drivers treat the work as meaningful supplemental income.
- Data-labeling providers and other gig platforms face a clearer incentive to place similar AI tasks inside apps that already have active worker networks, rather than acquiring contributors separately.
Third-order effects
- If this model proves repeatable, large gig platforms could increasingly turn their worker bases into on-demand inputs for AI-data operations, blurring the line between mobility marketplaces and AI-services infrastructure.
- That shift would make the economics of human-verified AI data more dependent on platform control of distribution and worker incentives, while raising enduring questions about task transparency and compensation.
The trend: Gig platforms are embedding AI-data work into existing worker apps to convert distribution and labor networks into AI-services capacity.