You're not wrong about grading being largely a numerical ranking system for resource allocation - with minimal effort from the allocator.

Even in the age of AI, I think I still prefer a portfolio system where you accumulate a body of work that you can present and defend in an interview for a job or graduate school position. Unfortunately diligent portfolio assessment can be a lot of work when there are hundreds of applicants for a single slot, so the first stage is usually reviewing a summary or list of work rather than the work itself, and that system can be gamed.

In any case, personalized feedback for student work is still very useful, and it may be more beneficial if it is focused on helping students individually rather than ranking them or sorting them into bins.

Without some sort of pre- and post-assessment, it can be hard to determine whether students actually learned anything in a course. The question is: how do you use that information? I think it should primarily be used as feedback to the students and the instructors, with the aim of improving learning.