Algorithmic Siege: China's Machine-Speed Rehearsal for Taiwan

Algorithmic Siege argues that the People’s Republic of China is compressing the timeline from reconnaissance to effect, using artificial intelligence to accelerate the tradecraft it rehearses against regional networks as pre-positioning for a potential 2027 Taiwan contingency. The paper reads recent activity not as isolated intrusions but as a machine-speed rehearsal of the operations that would matter most in a crisis.

The analysis examines how AI shortens each phase of an operation: automated reconnaissance across exposed infrastructure, faster identification of viable access, and coordinated persistence at a scale and tempo that outruns traditional defensive review. It contends that the same regional networks long used as a proving ground are now the testbed for AI-accelerated methods.

The brief connects this acceleration to strategic intent, showing how machine-speed pre-positioning inside communications, logistics, and energy systems is designed to constrain an adversary’s ability to mobilize and respond at the outset of a contingency. It treats the compression of the attack timeline as a warning indicator in its own right.

It closes with recommendations for defenders: build detection tuned to AI-accelerated tradecraft, shorten defensive decision cycles to match the adversary’s tempo, and share observations across allied networks facing the same rehearsal. It is published by the East West Strategic Research Collective on ResearchGate.