To bolster the argument, even if you do not plan to write the SIMD yourself or will "just get AI to do it", it is important to know what can be fast in SIMD (and on what hardware). That allows you to design your algorithms and structure your code so that the SIMD is possible.

Internalizing things like how data dependencies matter, how expensive it is to increase the width of your vector elements (and how to avoid the need), how to turn conditions and branches into masks, or simply things like "division does not exist" becomes a lot easier when you have spent at least some time trying to use SIMD yourself.