Measuring AI Security: Beyond Benchmarks and Standards

Securing artificial intelligence systems requires more than benchmark scores, according to security experts. Traditional software security approaches—from penetration testing to architectural risk analysis—may offer valuable lessons for AI security measurement. However, AI's deeper business impact demands adapted strategies. Rather than seeking a single security metric, organizations should focus on establishing robust assurance processes and risk management frameworks. The evolving field of AI security must learn from decades of software security development while recognizing AI's unique challenges. Experts emphasize continuous vigilance and proper process management remain essential, as no single security measurement can guarantee AI safety.