Integrating model validation involves incorporating automated tests that assess model performance and accuracy at each stage of the pipeline. This includes evaluating metrics like precision, recall, and F1 score in staging before deployment, while performance monitoring ensures that models are evaluated in production against real-world data to catch any drift or degradation.