

The main issue for the company is that he’s having an affair with a person directly under him in the company - it’s a conflict of interest at the very least, with the possibility of the person higher up in the hierarchy having leveraged their position to get sexual gratification from their underling and/or of the underling having used their sexuality to influence that higher up in the professional domain (for example, to get salary raises).
Absolutely, they might both be impeccably professional and not let their romantic relationship influence their professional relationship, but the company doesn’t know that and it’s hard to disprove that it wasn’t so.
On the Moral and Ethical plan, the main issue is indeed that they’re betraying their respective partners in secret rather than having assumed their relationship.
“Intelligent” is itself a highly unspecific term which covers quite a lot of different things.
What you’re think is “reasoning” or “rationalizing”, and LLMs can’t do that at all.
However what LLMs (and most Machine Learning implementations) can do is “pattern matching” which is also an element of intelligence: it’s what gives us and most animals the ability to recognize things such as food or predators without actually thinking about it (you just see, say, a cat, and you know without thinking that it’s a cat even though cats don’t all look the same), plus in humans it’s also what’s behind intuition.
PS: Way back since when they were invented over 3 decades ago, Neural Networks and other Machine Learning technologies were already very good at finding patterns in their training data - often better than humans.
The evolution of the technology has added to it the capability of creating content which follows those patterns, giving us things like LLMs or image generation.
However what has been made clear by LLMs is that using patterns alone (plus a little randomness to vary the results) in generating textual content is not enough to create useful content beyond entertainment, and that’s exactly because LLMs can’t rationalize. However, the original pattern matching stuff without the content generation is still widely used and very successfully so, in things from OCR to image recognition.