Generative AI is already in use in many companies, often faster than the matching safeguards. Classic security tools see only part of what AI applications do.
An AI application processes input, context and often external data in real time. That is exactly where attack surfaces appear that a traditional firewall or a classic endpoint tool does not cover. Prompts can inject instructions, sensitive content can end up in models by accident and output can be manipulated on purpose.
Employees use public AI services without approval. The first step is therefore rarely a new tool, but visibility into where AI is already being used.
Hidden instructions in input or documents make the model bypass its rules.
Sensitive information enters external models through input and leaves the controlled environment.
Faulty or manipulated answers flow into processes and systems unchecked.
Agents with excessive permissions perform actions no one approved.
Visibility into which AI services, models and agents are used, with which data and interfaces.
Suspicious behavior, risky prompts and data leakage are detected before damage occurs.
Guardrails, access rules and policies take effect directly at application runtime.
The result is not a ban on AI, but controlled use that fits the maturity of the organization.
