I think the answer is very simple:
Python is a very simple language, with a lot of consolidated libraries in the area (Scikit-learn, Numpy, PyTorch, Keras, OpenCV .API …). The majority of pre-processing algorithms are also available in Python (as sci. The Julia equivalents are, obviously, not so complete yet. Also, many researchers in the AI area are reluctant to learn another programming language (Python is the easier).
Also, the performance topic is not important for many (when the training/evaluation takes a lot the performance of the rest of the system is not so important).
Another important is the spread of the language. In research you want to collaborate, and make your algorithm/technique available. Python is a lot more known than Julia, and you will have more influence making available your proposal in Python.