Methodologies and practices for testing AI models in terms of accuracy, reliability, security, and compliance. Includes functional testing, performance validation, bias and fairness analysis, robustness verification, security testing for AI-specific vulnerabilities (prompt injection, model inversion, data leakage), and behavior evaluation in real-world and adversarial scenarios.