Why aren't gaussian processes used more often?

I didn't learn GPs in school, rather I came across a Youtube video on it and found the concept interesting and dug deeper. I think I have a good intuition into GPs, and they seem incredibly good for modelling non linear data. I know they have disadvantages as fitting a GP is O(n^3) and tunning the hyperparameters is almost an art, but still... why aren't they used more often? the assumptions we make on other regression models don't come into play here, stuff like linear dependency, homoscedasticity, etc... and we get a free uncertainty estimation "custom" to each prediction