[spekcular]

AIC is an estimate of prediction error. I would caution against using it for selecting a model for the purpose of inference of e.g. population parameters from some dataset (without producing some additional justification that this is a sensible thing to do). Also, uncertainty quantification after data-dependent model selection can be tricky.

Best practice (as I understand it) is to fix the model ahead of time, before seeing the data, if possible (as in a randomized controlled trial of a new medicine, etc.).

[ramblenode]

And it is not uncommon that an intentionally bad model (low AIC) will be used for inference on a parameter when one wants to test the robustness of the parameter to covariates.