outlier detection: zscore vs isolation forest

Trying to understand when to use zscore and when to use isolation forest for determining outliers in the data.

I know that zscore is only applicable if data is normally distributed whereas isolationforest doesn't require data to follow any distribution.

However let's say if data is following a normal distribution then will there be any benefit to using isolation forest?

Also ,aside from normal distribution , what would be some other reasons to choose one over the other ?

thanks