I've heard of some database migration tooling that uses category theory to compute robust data transformations that are automatically composable to achieve the desired outcome.

There has been seen some research into the fundamentals of machine learning, using category theory approaches for computing the compositions of transformations of expressions. E.g.: simultaneously computing a gradient, the "bounding box" of the error, and other similar derivatives to improve the robustness of gradient descent.