There is a lot of confusion about CUDA and OpenCL, but especially GPUs floating around. The most important facts to get you thinking:
1. GPUs computations are very fast at certain, but not all, tasks. They will be faster than your CPU if the task is easily parallelizable to many (about 2000) cores, and/or if it uses operations that are well implemented on GPU architectures, like sines/cosines or shader operations.
2. A big problem on most systems is the bandwidth to the GPU memory. To get something calculated on the GPU, you have to copy all necessary information from your CPU RAM to your GPU VRAM, and that can take a long time.
So: For many tasks, the GPU is pretty efficient and will make things faster. But if you have to send around a lot of data (like for compressing an HD video), or if you have jobs that don't parallelize well (like matrix inversions), it might be better to do those things with the CPU.
If a software is programmed cleverly (and the Adobe ones certainly are), it will not exclusively use the GPU for everything it does, but distribute appropriately to exploit the advantages of CPU and GPU architectures.
Does that help you in any way? I had the feeling you were expecting the wrong things here...
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Oh, additionally: This seems to really bug you. But it's all working, is it not? I hope that you can somehow let go and just trust Adobe and your CPU/GPU to do the work they are supposed to.