Enterprise AI security is the practice of protecting AI systems, the data they use, and the business tools they connect to inside an organization. It covers model access, prompt handling, training data, logging, identity controls, and the APIs or workflows that let AI reach files, apps, and users.
This matters because AI can widen the attack surface. If an attacker steals credentials, abuses a chatbot, poisons data, or tricks a model into revealing sensitive information, the impact can spread across multiple systems. Defenses include least-privilege access, data classification, approval workflows for AI services, monitoring for unusual prompts or outputs, and clear governance for how models are deployed and updated. In practice, enterprise AI security makes AI usable without letting it become an unmanaged security risk.