TL;DR
The practice of systematically probing AI models to identify security vulnerabilities, biases, and safety risks through simulated adversarial attacks.
AI red teaming involves human security researchers or automated agents generating deceptive, complex, or malicious inputs to force a model into bypassing its built-in safety guardrails. The process aims to uncover hidden flaws such as jailbreak vulnerabilities, hallucinations, and privacy leaks before a model reaches production. This proactive testing allows developers to iteratively patch defensive barriers and improve systemic alignment.
Why this matters for your business
It operates as a critical line of defense for enterprises, ensuring that generative models comply with security standards and do not produce harmful or legally risky outputs.
