You're assuming that an inscrutable AI is basing its decisions off of something you can change on your CV.

Maybe it doesn't like your name, one of your past employers, or Oxford commas. It's effectively a black box, so who knows?

Well sure, but HR people are not less of a black box either.

People have well-documented biases, besides reflecting biases of humans, AI systems will also have arbitrary biases that are hard to predict.

CVs are already a horribly low signal - people lie way too much on them. I wouldn't expect AI to take into account anything you personally put on paper. Just like insurance/credit score AIs don't care about what you put down on papers much.

I believe you're missing the whole point. AI is often used as a fancy name for classifiers in general, including supervised and unsupervised learning algorithms.

Filtering the initial batch of candidates is basically a classification problem. It is also very time-consuming to perform by hand.

If recruiters are able to used supervised/unsupervised algorithms to filter out 90% of the initial candidates with a low misscladsification error and without wasting valuable time the they'll be able to operate more efficiently.

The trick is how to tell how far the auto classification algorithms should go in helping pick the best candidates. Some company use stupid fizzbuzz tests to weed out candidates based on a quantifiable index by abusing a metric whose value is negligible but very effective in weeding out a considerable portion of initial candidates.