Unless something dramatic changes and it'll become cheap to "constantly re-educate" the models to learn the new fundamental facts about the system (ideally with a small lag of maybe a few days like with humans) I see no reason to think that LLMs can have a profound understanding of how business systems work of a remotely comparable quality to humans. Just adding the context about the system already reduces it's capacity significantly according to what I can tell. Not having large context helps somewhat at a cost of having to explain lots of task-relevant things to LLM over and over again...
> I see no reason to think that LLMs can have a profound understanding of how business systems work of a remotely comparable quality to humans
My manager was dragging me through useless projects that went nowhere despite multiple people telling him "it ain't gonna work" while shooting down proposals that later turned out to be "high priority tasks required directly by upper management". And he's a well-paid, educated employee with years of experience. Don't even get me started on delivery guys who cannot read a simple instruction like "do not ring the bell, leave the package on the doorstep". They just follow a 50-line script and that's all they can do.
Whenever you mention that AI won't reach human intelligence, remember that this is the benchmark. Not Alexander the Great, it's the millions of people throwing their life savings ($1000 each) into Labubus. Long time ago there was a series of articles in my country about the costs of wedding receptions skyrocketing and some people taking out loans to pay that, and someone made a meme "robots will never have human intelligence!" with reply "bro, you took out a loan to pay for a wedding, I don't want your human intelligence".
Denying this reality is pure cope.
Online / continual learning will solve this problem. Test time training has already proven to be effective.