A structured approach to testing AI systems by having dedicated teams attempt to find flaws, vulnerabilities, harmful outputs, or other potential issues before deployment. Red teams adopt an adversarial mindset to uncover weaknesses that might not emerge during standard testing.

Red teaming provides a crucial layer of safety testing for AI systems, particularly for high-risk applications or capabilities. Unlike conventional testing that focuses on expected functionality, red teaming explicitly seeks to uncover edge cases, potential misuses, and unexpected behaviours. Effective red teaming combines technical expertise with diverse perspectives, including ethical considerations and domain-specific knowledge. Findings from red team exercises inform model improvements, safety guardrails, and deployment decisions.

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A financial services company employing a red team to systematically probe a new AI-powered investment advisor, testing whether it could be manipulated into recommending un