This is pretty much the opposite of what I’ve been seeing for the last few years. Generally DL models will be simpler because you don’t need as much feature engineering, and they will generally be more interpretable because they’re more accurate. Logistic regression is just a neural net with no hidden layers. There are not that many problems where zero is the appropriate number of hidden layers.
You’re not going to get a 90% accurate object detection system in your self-driving car using logistic regression.