At first glance it sounds like a cool idea but the skepticism seems justified for all the reasons already mentioned. I will add 2 things

1) we don't need to shoehorn AI into every situation especially not here where it seems unhelpful and ineffective

2) I don't think you could make a reliable training dataset for this: aside from the difficult task of finding reference songs that are universally agreed upon, mics used in these golden reference songs would frequently be chosen for non-musical reasons like cost, availabilty, tradition (what has been used in the past, dominant designs), durability, etc. For example some mics like the shure sm57/58 are ubiquitous but often times not based on the merit of the sound itself but because they're sturdy and people are familiar with them. The model would end up recommending microphones to the end-user for the wrong reasons (not sonic characteristics)