Multimodal data offers improved accuracy and robustness because different modalities provide complementary information that can compensate for weaknesses in individual modalities. It also allows for handling missing data by leveraging information from other modalities. However, multimodal systems typically have higher computational complexity and may require more sophisticated data preprocessing and feature engineering. While they can be more robust, the complexity can also potentially introduce new vulnerabilities, especially to adversarial attacks.