Gaussian elimination isn't that bad, is it?

Important concerns include the size of your matrix, any qualitative properties it may have (such as sparse, symmetric, or banded), and what you want to do with the inverse.

For example,

the conjugate gradient method is well suited for solving the equation Ax=b when A is large sparse matrix, but it won't explicitly compute A inverse.