The fact there is no moat makes things far more dangerous. When LLMs start acting like weapons governments will treat them like weapons much to your dismay, crying, and gnashing of teeth as your door is kicked in and you're dragged out by armed men for running one.
Cast away your preconceptions for one moment and think "What will the future look like if LLMs are/can be actually dangerous".
But that doesn't take away from the real issues and dangers AI poses?
As the frontier gets smarter and more useful prices will only go up, as they are set to replace jobs being paid six or seven figures a year - the demand for as much inference on these models for as long as possible will be astronomical, but compute starting in 2030 will not be keeping up.
Eventually prices will fall for assistants but the frontier will be the most profitable thing in the world, and the top companies basically already have oligopolies due to their ridiculously expensive compute investments.
Train: yes, for now.
Host: depends on the scale. At a small scale a wealthy individual could easily build a rig in their basement to host one of these things. At larger scale any cloud company could do it, and many already have the compute on site. At large scale this is true... again, for now.
What you say only holds (in the absence of a state oligopoly) if two conditions are met: (1) AI performance does not asymptote any time soon due to running out of training data or other scaling limitations, and (2) these companies are able to stay at the frontier.
There's little to no moat, so staying at the frontier will be a game of investing massively in compute, talent, and R&D, and they can never stop.