CONCEPT
Market Tipping
The phenomenon by which markets with strong network effects converge on a single dominant platform — and after which the dominant platform's position becomes self-reinforcing and reversal through regulatory intervention becomes prohibitively costly.
Tipping is the economic term for the process by which a market exhibiting positive feedback from network effects crosses a threshold beyond which the leading platform's advantage becomes self-sustaining. Before tipping, multiple platforms compete; after tipping, one dominates. Shapiro's work with Katz formalized the mathematical conditions under which tipping occurs and identified the policy consequence most relevant to the AI transition: the window for effective antitrust intervention closes at the tipping point, because the costs of reversing an established dominant position multiply rapidly once network effects have consolidated the market.
In The You On AI Field Guide
The dynamic was formalized in Katz and Shapiro's 1994 paper Systems Competition and Network Effects, which demonstrated that positive feedback in network markets creates thresholds beyond which the leading platform's advantage becomes self-sustaining. Before the threshold, the market's competitive structure is genuinely contested. After the threshold, the market converges on a single dominant standard through mechanisms that no individual firm or regulator