Noooooo, not like that! Automation is only for people who didn't go to Harvard!

The funny thing is, the only barrier here is context size. Right now, LLMs have laughably bad context size (or attention spans, in human terms, it's basically how much information a Brian or model can keep active at any point in time) compared to humans, but that's going to change. It's not difficult to foresee a near future of LLMs with very, very, superhumanly large context sizes that could make human leadership seem ridiculously incompetent in comparison. Here's the thing, pyramid-like organizational structures are extremely common because we necessarily have layers of abstraction; the head of the organization can't do their job effectively if they're worried about whether Bob the Welder is going to make it in on time or if that invoice has got paid yet; likewise, Bob the Welder can't do his job if he's getting pulled off work to go sit in marketing meetings all day. There's only so much attention any one person can give in a day. The biggest problem is that information gets lost between these layers of abstraction, values don't necessarily remain consistent, and policies and practices aren't uniformly applicable, which can make it difficult for customers and even employees to navigate the normal processes of an organization, let alone the abnormal ones.

As LLM context sizes reach superhuman levels, it's conceivable that they could end up flattening organizational structures by being able to be both Bob's supervisor and the CEO (or at least the CEO's assistant), and being able to keep all of the organization's context, down to the individual employee and customer needs, in mind at all times when making decisions. A government or corporation run by a properly aligned super-context AI could possibly be the closest thing we're going to get to utopian leadership, and would likely be both more ethical and more effective than human leadership.