For decades, cybersecurity teams have relied on the “patient zero” model: one organization is hit first by a new attack, the industry studies it, and defenses are then deployed to protect others. This approach worked in a pre-AI threat landscape. In a post-AI world, however, it is increasingly ineffective. AI allows attackers to continuously mutate their techniques, so by the time an attack is analyzed, and defenses are rolled out, subsequent attacks look fundamentally different from the original. As a result, defenses based on prior incidents fail to keep up. Attacks now evolve at such speed that, in practice, every organization becomes patient zero. This session will take a technical deep dive into the limitations of patient zero detection in the face of AI-enabled adversaries. We’ll examine how threat actors use automation to launch simultaneous, polymorphic attacks and why organizations must shift toward preemptive defense models. Attendees will gain insight into the latest research and frameworks for building resilience against next-generation threats.