Synthetic Panic: Effect of AI-Driven Synchronization on Financial Fragility

Can AI-driven amplification of belief synchronization produce coordination failures in financial markets whose fundamentals are sound? This paper develops a formal framework combining a reduced-form Kuramoto model with a Morris–Shin coordination game. The belief layer specifies two channels of AI influence: directional content forcing, which pulls sentiment toward a speci- fied narrative phase, and coupling amplification, which strengthens peer-to-peer interaction rates without imposing a narrative direction. The model identifies a synthetic-panic region in which AI-driven belief synchronization causes market failure even when fundamentals are sound. Be- cause retail and institutional investors respond differently to synchronized sentiment, retail selling can endogenously erode fundamentals until institutional investors rationally capitulate, produc- ing a two-stage cascade. The two-channel specification also implies that adversaries can rely less on visible directional content when markets are most fragile. The framework generates testable predictions linking volatility, synchronized sentiment, retail flows, and institutional exit.