In the aftermath of 9/11 security agencies augmented their counterterrorism (CT) apparatuses with advanced analytics, machine learning (ML), and artificial intelligence (AI) to improve their ability to identify and neutralize terrorists. Under this regime, humans remained the central actors, tasked with understanding information and crafting a response. The advent of Generative AI (GenAI) changes this equation. GenAI’s ability to mimic humanity’s reasoning skills augurs a world where machines assume responsibility for most CT activities. This possibility raises fears of machines outside of human control. These fears are currently unfounded, and to the extent that they’re real, they must be weighed against the ability to reduce the victims of terrorism. As this world forms, what will matter more is decision-makers’ understanding of AI/ML outputs for counterterrorism, as they will have to make strategic choices around a series of ethical and policy choices that are inherently human. This article explores this subject more in-depth, reviewing the evolution of AI/ML and its impact on different CT domains, exploring the strategic dimensions of AI/ML, and concluding with a series of policy recommendations.