GAs are in this weird place where much of their lunch (by which I mean tasks such as classification and regression), has been eaten by more principled methods from Machine Learning.

They've also been pushed out of most combinational optimisation problems by Constraint Programming methods and by other more principled meta-heuristics such as Large Neighbourhood Search.

In my opinion part of the problem is that so much of the literature around GAs involves what I like to think of as voodoo optimisation. You take a simple to implement randomised algorithm, apply it to some poorly studied but high-dimensional problem and then poke things as appropriate until you eventually find some feasible solution. Maybe.

If I'm being honest, the only time I'd consider GAs is if I had very little insight into the problem at hand and even then only after I've run out of other things to try.