With the ability to see what everything in an image is, there are endless possibilities of what it can do. Semantic segmentation is the first "comprehensive" computer vision technology where one gets information about the whole image.
The upside is that it provides a clear boundary between two objects of different classes. Ex. road surfaces and the sidewalk when used for driving, in a way that object detection
does not. The downside is that semantic segmentation does not separate objects of the same category that overlap.
Suppose one needs pixel-level predictions and the ability to distinguish between objects. In that case, instance segmentation
might be worth looking into, or if one is primarily interested in identifying objects for example tracking object detection
is worth a look.