A data flywheel is a self-reinforcing loop where customer use of an AI product generates proprietary data that improves the product. Better product drives more customer use, which generates more proprietary data, which improves the product further. Each turn of the loop makes the product better and the moat stronger, making the data flywheel the most powerful and durable AI moat available to startups because every iteration compounds. It's why Google search keeps getting better, why Tesla's autopilot improves with each car driven, and why vertical AI startups can compete with foundation model giants.
The four-step cycle: