Those measures help reduce the potential impact in the event an AI system behaves unexpectedly. Liebig argued that organizations need to examine every potential "influence path" through which an AI system could expand its reach. He argued that many current AI security approaches rely too heavily on software-level controls such as application guardrails and prompt restrictions. Building confidence as AI adoption acceleratesThe challenge for CIOs is developing enough confidence to deploy AI systems while maintaining control over the risks those systems introduce. That will require AI security practices to mature alongside adoption; Lohrmann described today's enterprises as "entirely unprepared."