Robustness

The ability of an AI system to perform reliably across a wide range of conditions — including inputs the system was not specifically trained on, adversarial inputs designed to cause failures, edge cases, and environmental variations. A robust AI system degrades gracefully when faced with unexpected inputs rather than failing catastrophically. The EU AI Act requires high-risk AI systems to be accurate, robust, and cybersecure. For small teams, robustness testing means evaluating AI tools on realistic edge cases before deployment, not just on the ideal-case scenarios shown in vendor demos.