Is catastrophic forgetting bad for specific use cases?

Correct me if I'm wrong but my understanding is that CF happens when a model forgets its previous capabilities when training on a new task.

However if you want a model that is highly optimised for a single task, isn't this acceptable? Or is there something else at stake, such as the understanding capability?

capabilities cases catastrophic forgetting deeplearning however isn something training understanding use cases