There are lots of discussions and explanations of what it means to be "Bayesian," but I think the best thing to do is jump in and start building models. That is how I came to understand the utility of Bayes.

If you're looking for a place to start I'd go to Andrew Gelman's introduction for the Stan Language: https://www.youtube.com/watch?v=T1gYvX5c2sM

There are Stan implementations in R, Python, Julia or you can run it in C++ since it's written in C++. I think this has greater potential to change how we deal with the unknown than AI or other machine learning.