While AUC is a powerful metric, it is not without limitations. One major limitation is that it does not take into account the actual costs and benefits of different types of errors. For instance, a false positive may have a different impact than a false negative, but AUC treats them equally. Additionally, AUC is not very informative when dealing with highly imbalanced datasets, which is often the case in email marketing.