CONCEPT
Network Effects
The economic phenomenon by which a good becomes more valuable as more people use it — formalized by Katz and Shapiro in 1985 and now the single most important concept for understanding AI platform market structure.
Network effects arise when the value of a product to each user increases as the number of other users grows. Katz and Shapiro's 1985 paper Network Externalities, Competition, and Compatibility formalized the mathematics of this phenomenon and established the theoretical foundation for understanding how network goods tip toward dominant platforms. The framework identified two canonical forms — direct effects (value scales with co-users, as in telephones) and indirect effects (value scales through complementary goods producers, as in operating systems). The AI platform market exhibits a third form, the data network effect, whose compounding dynamics have no precise precedent in previous information markets.
In The You On AI Field Guide
The canonical example of a direct network effect is the telephone. One telephone is useless; a million telephones constitute a communication infrastructure. The value scales with adoption, creating a positive feedback loop — more users make the network more valuable, which attracts more users, which makes it more valuable