AndrewKao
Andrew Kao is a PhD student in economics at Harvard University. His research focuses on the political economy of new technologies, such as AI and the internet. His website is https://andrew-kao.github.io/
Session
As artificial intelligence becomes a pillar of economic and strategic power, AI labs are emerging as the next high-value targets for espionage. State and corporate actors have compromised other critical sectors, such as semiconductors, aerospace, and biotechnology, for decades to steal trade secrets and shift global advantage. In this talk, we present findings from a new analysis of over 200 historical cyber and non-cyber espionage incidents across various industries. By mapping attack patterns, ranging from insider threats to IP theft, to the realities of AI infrastructure, we demonstrate how the same vulnerabilities now apply to AI labs, particularly around sensitive assets such as model weights, training pipelines, and proprietary data. Drawing from these cross-sector case studies, the talk distills actionable lessons for AI organizations and introduces a tailored threat evaluation framework. We also demonstrate how AI-related IP theft differs from other sectors due to the extraordinary potential for economic and strategic power gains, which is likely to heighten the incentives of attackers and increase the risk to AI organizations.