It's worth it whenever you have a reasonable amount of training data. You can get substantial quality improvements automatically. Unless you're doing some kind of prompt-optimization, prompt-tuning is a lot of random guessing and trial-and-error. It's also most necessary when you have a smaller base model, as opposed to one of the big ones.