I'm not going to say that ML is a panacea or always perfect but its also not one "thing". It's a complex field with a lot of required knowledge and ways to set

I'm not going to say that ML is a panacea or always perfect but its also not one "thing". It's a complex field with a lot of required knowledge and ways to set things up. IBM is largely to blame for that misunderstanding since they brand all of their offerings "Watson" and describe it as if it's one system; so if their system doesn't work, maybe none will. In reality, it's dozens of pre-implemented algorithms with varying degrees of quality. Importantly, how the data interacts with those algorithms requires domain expertise for the data and algorithms so it can be hit-or-mess if that expertise is not properly applied.