Your question is very hard to answer in it's current form. You want to know why GPU utilisation is not 100%? The answer is, because the GPU isn't running kernels 100% of the time. Why? I don't know, because you haven't provided any information about what you're doing. Maybe, as Walter says, a lot of time is being spent doing file I/O, perhaps because you have a very slow disk or slow network file access. Maybe you have a transformed datastore, or an imageDatastore with a custom ReadFcn, and the data processing is very complex and takes place on the CPU, blocking GPU execution while it is carried out. Maybe you have a very small network, or a low resolution network, or you don't have a high enough mini-batch size, and so you are not successfully occupying all the cores on the GPU. Maybe your network is so small that the amount of time spent running the MATLAB interpreter in order to generate the GPU kernels to do the computation outweighs the amount of time it takes to run those kernels.
If you want to know more, run the MATLAB profiler and find out where time is being spent during training.