What happened
RAND researchers developed and ran Camp(ai)gn, an unclassified operational-level wargame exploring how AI-enabled autonomous systems could change campaign planning and execution, played across ten iterations of a hypothetical 2035 U.S.-China conflict over Taiwan by more than 20 RAND researchers and affiliates. Authors Zachary Burdette, Barry Wilson, David R. Frelinger, Hiwot Demelash, and Julia Arnold report six observations, including that autonomous systems could enable distinctive 'limited conflict' escalation dynamics, that 'autonomous mass' could favor China in protracted conflicts, and that attacking an adversary's data centers 'is unlikely to deliver decisive operational effects.' The authors explicitly frame the findings as gameplay-generated hypotheses, not established conclusions.
Why it matters
Offers defense planners and national-security policy teams an early empirical signal on how AI-enabled autonomy could reshape escalation dynamics and infrastructure-targeting assumptions in a great-power conflict scenario.
Action needed
Flag for national-security and defense-industrial policy teams tracking AI-enabled warfare planning assumptions and allied-integration implications.