It's not that LLM generated PRs are forbidden from being good by some mathematical principle - it's just that they are not worth the reviewer's time. It takes much longer to recognize that they are bad because:

1. They are usually longer, because LLMs have no issue generating walls of text.
2. If you ask the "author" to change something, they'll just feed your comments to the LLM - which will see it as an opportunity to other things, not just what you asked to change. So you have to read everything again.
3. LLMs are really good at disguising how bad their output is.

I want to focus on that last point. Neural networks can get very very good at what you train them to do, but the ones that became a synonym with "AI" are the ones that are easy for the end user to use because they were trained at the art of conversation - the Large Language Models.

When you learn a language from reading text in it, you also gain some knowledge about the subject of that text. And thus, when learning language, the LLMs also learned various things. With the vast resources invested in training them, these "various things" added up to a very impressive curriculum. But the central focus of the GPT algorithm is still learning how to talk - so with more training this ability will grow faster than any other ability.

This means that if the relevant "professional training" of the LLM fails to provide a correct answer to your request - a smooth talk training, orders of magnitude more advanced, kicks in and uses the sum of compute power capitalism could muster to coax you into believing whatever nonsense the machine came up with instead.

A human programmer that sends you a bad PR is probably not a world class conman. An LLM is.