The python runtime is slow in general. But anyone using it for ML is not actually using the python runtime to do any of the heavy lifting. All of the popular ML/Ai libraries for python like tensorflow, pytorch, numpy, etc. are just thin python wrappers on top of tens of thousands of lines of C/C++ code. People just use python because it's easy and there's a really good ecosystem of tools and libraries.
Sure, Python can make you start fast with any ML project, but when you have to deal with heavy-duty tasks, a switch to pure C++/Rust/Any-Compiled-Language implementations might be a good investment in terms of performance and cost-savings, especially if the above heavy tasks are done in any cloud platform