DoorDash has introduced a new standalone application called “Tasks,” aimed at turning its vast delivery workforce into contributors for artificial intelligence development. The platform allows couriers, known as Dashers, to earn additional income by completing small assignments such as recording videos, capturing images, or submitting audio clips that can be used to train AI and robotic systems.
The initiative reflects a growing trend in the tech industry where companies are sourcing real-world data directly from distributed workforces. Through the Tasks app, Dashers can perform activities like filming everyday chores, recording conversations in different languages, or documenting real-life environments. This type of data is particularly valuable for training AI systems to better understand real-world scenarios that are difficult to replicate in controlled settings.
According to the company, the data collected will be used not only to improve its in-house AI models but also to support systems developed by partners across sectors such as retail, hospitality, insurance, and technology. The goal is to enhance how AI interacts with the physical world, from understanding human actions to improving automation and robotics capabilities.
The Tasks platform operates in two formats: a standalone app for independent assignments and additional task listings within the existing Dasher app. These tasks range from capturing photos of restaurant dishes for digital menus to documenting locations like hotel entrances to improve delivery accuracy. In some cases, Dashers may also assist in operational tasks linked to automation, such as interacting with self-driving delivery systems.
DoorDash stated that compensation is displayed upfront and varies depending on the complexity and effort required for each task. This creates a flexible earning model where couriers can choose assignments based on their availability and preferences, effectively adding a new income stream alongside traditional delivery work.
The move highlights how gig economy platforms are evolving beyond logistics into data-driven ecosystems. By leveraging its network of over 8 million Dashers, DoorDash is positioning itself as a large-scale provider of real-world data, which is increasingly in demand as AI systems require diverse, high-quality training inputs.
The launch also places DoorDash among a growing number of companies exploring similar models. Competitors such as Uber have experimented with allowing drivers to complete microtasks like uploading images to train AI systems, signaling a broader shift toward integrating gig workers into the AI value chain.
However, the approach raises questions around data ownership, privacy, and fair compensation. Since many tasks involve recording personal environments or daily activities, concerns have emerged about how this data will be stored, used, and monetized. Additionally, the long-term implications of gig workers contributing to technologies that could eventually automate parts of their own jobs remain a point of debate.
Currently, the Tasks app is available in select regions in the United States, excluding areas such as California, New York City, Seattle, and Colorado. DoorDash has indicated plans to expand both the range of tasks and geographic availability in the future, as it continues to build a scalable pipeline for real-world AI training data.
As artificial intelligence systems increasingly rely on real-world inputs, DoorDash’s new initiative illustrates how everyday human activity is becoming a critical resource in the development of next-generation technologies.
