Security teams are firefighting vulnerabilities in an environment where AI systems operate fluidly and autonomously, creating a growing risk if security is not adapted to the new paradigm.

Organizations are deploying AI rapidly, often skipping traditional enterprise lifecycle stages and integrating APIs, models, and data from diverse sources.

AI adoption is accelerating across products and processes and in boardroom discussions, yet security practices are lagging behind.

This rapid, interconnected, real-time, multi-layer deployment forms a dynamic tool that spans the stack, demanding a fundamental rethink of security.

Traditional security approaches suited to older architectures are being inappropriately applied to AI systems, creating gaps as organizations extend controls without addressing core differences.