For most established tasks people have a good idea (based on empirical evidence) about the limits of particular methods for this task.

There are tasks where "traditional machine learning methods" work well, and people working on these tasks use them and will use them.

And there are tasks where they don't and deep learning gets far better results that we could/can do otherwise - and for those types of tasks, yes, it would be accurate to say that we have given up on traditional machine learning; if you're given an image classification or text analysis task, you'd generally use DL even for a simple baseline without even trying any of the "traditional" methods we used in earlier years.