AI Security Broken at Runtime: Enterprises Unaware

AI security is currently broken at runtime, and most businesses don't realize it. While AI systems have rapidly advanced, the methods used to secure them have not kept pace. Many organizations still apply traditional security models to AI, which creates a critical gap when these systems are actively working. Here's the thing: enterprise security has largely focused on data that is stored or moving. But there's a third, less protected state: data in use. When an AI model runs, sensitive data, including valuable intellectual property and real-time information, is actively processed in memory. This data can become visible to the underlying system, even in otherwise secure environments. The issues often emerge deeper in the AI lifecycle, not from perimeter defenses. This includes the training phase, where sensitive information can leak into models or be retained unintentionally. It also impacts inference, which is when inputs become outputs. This matters because it means valuable AI assets are vulnerable at the very moment they are being used.