Anecdote: I've had at two friends publish "papers" just by slapping their names on something they had literally nothing to do with, out of pure nepotism.

This wouldn't be helped by an AI watermark. What would help is if the reviewer used AI to look up the authors and see the authorship claims are dubious. The papers are still up.

I do think the academic publishing field is corrupt, which is why I'm not convinced it should be on AI providers to help bail it out of doing its one job (verification and trust).

Verifying authorship is an ambiguous task. How much involvement is necessary to qualify for authorship? If someone reads the paper and gives some small feedback, is that enough? What if they were present in one meeting and raised a question that turned out not to be interesting? What if they have no clue about the work but helped with data validation?

I'd argue all of these could justify authorship, even if they're just in the middle of the author list. At least in NLP, which can be seen in the generally high number of authors in papers.

The standards also vary by field. It's not unusual for supervisors to be the last author on any paper that a group publishes, even if they had basically no input into it directly. I've been listed on papers just because I designed and built the equipment that happened to be used for the experiments, even though I didn't do anything but a quick review of the actual paper. For most papers, unless there's an indication otherwise, it's generally only safe to assume the first author listed that actually did the bulk of the work and write-up, and the others are there mainly for having some potentially quite indirect contribution.

I agree completely. That's why I pushed back on "nothing to do" from the OP. Maybe it was a small contribution, but calling it "corruption" is ridiculous.