Why You Need to Red Team Your Enterprise AI

AI red teaming is a form of deliberate adversarial testing designed to make an AI system fail in order to find and patch vulnerabilities before users encounter them. Unlike simple model testing, system-level red teaming evaluates the entire production application, including data retrieval, tools, and agent orchestration. Research shows that ordinary, non-adversarial users can cause system violations almost as frequently as skilled attackers, highlighting the need to test for a wide range of user behaviors. An effective testing process requires a written harm taxonomy defining specific violations for the system and a continuous cycle of testing, patching, and re-testing. A case study demonstrated this gap, where human testers found a 68% violation rate compared to just 3% from automated tests.