AI red teaming helps organizations test system safety

AI red teaming is a method for testing artificial intelligence systems under adversarial conditions to find security and safety weaknesses before deployment. The article explains that these tests simulate attacks such as prompt injection, data manipulation, and attempts to bypass guardrails in models, agents, and connected tools. The piece says the practice is becoming more important as AI use expands and incidents rise. It notes that red teaming can help organizations improve model security, support compliance with frameworks such as the NIST AI RMF and the EU AI Act, and strengthen incident response and system resilience. The article also highlights several consulting providers that offer AI red teaming services, including CBIZ Pivot Point Security, Reply, and Mindgard. It says choosing a service depends on how well it covers the full AI stack, how realistic its attack simulations are, and whether it supports ongoing testing and governance.