Perhaps, but I imagine that it would be difficult for the receptionist to spec such tools sufficiently such that they would want to use the tool. Also, how would this tool be distributed or accessed? Most people don't have package managers or even desktop environments that they can meaningfully modify. To use your example, the receptionist is likely running windows on a thin client that is maintained by an msp, so how would they install and use the tool?
People talk about AI solving coding, sure, to a large extent. The problems of design and ops completely confound the layperson. Just last year, a cousin mentioned they were using like lovable or something to build a webpage for their business idea. I offered to just throw it together for them, very simple crud. They gave me what they had on lovable, and they got no further than the landing page before they had no idea what to ask for, let alone how to ask for it. Prompts were literally "ok so now make the app" and the models like "well what about x y z"? You have to be technically inclined at the very least to get something remotely useful out of these things.
Edit to say that the best way such a person might use llms to make work easier is through whatever client they are provided, probably copilot, to do toil like data entry, scheduling, etc. but those lock you into that ecosystem and interface, and the solution:problem ratio is close to 1; one cannot extend or modularize such solutions because the concept isn't even in such a person's head. Perhaps this will be solved in time, but we are not there yet, and we're not close.
Deployment is only an issue because it's assumed to be unnecessary in a current environment. As that assumption changes, so will the default setups. Of course that introduces new vulnerabilities, but as LLMs also make a mess of everything security related (and future LLMs will likely make a mess current era 'LLM hardened' setups, onward) our approach towards security and the internet will change in ways that are difficult to predict today.
I agree that plenty of people are currently hesitant to use LLMs for technical purposes, but I don't think it's because they literally could not do it. LLMs will now code up entire workable apps from minimal/vague/contradictory descriptions. If somebody only got to a landing page it's because they only prompted for a landing page, possibly trying to mimic how a human developer might have previously built a site - and quickly getting lost. But if you just say 'make a website where people can order widgets, manage their orders, and do all related tasks' it'll get done, no technical knowledge needed.
So I think we're mostly in a transitory phase. As people realize how powerful these tools have become, adoption is simply unavoidable.
People talk about AI solving coding, sure, to a large extent. The problems of design and ops completely confound the layperson. Just last year, a cousin mentioned they were using like lovable or something to build a webpage for their business idea. I offered to just throw it together for them, very simple crud. They gave me what they had on lovable, and they got no further than the landing page before they had no idea what to ask for, let alone how to ask for it. Prompts were literally "ok so now make the app" and the models like "well what about x y z"? You have to be technically inclined at the very least to get something remotely useful out of these things.
Edit to say that the best way such a person might use llms to make work easier is through whatever client they are provided, probably copilot, to do toil like data entry, scheduling, etc. but those lock you into that ecosystem and interface, and the solution:problem ratio is close to 1; one cannot extend or modularize such solutions because the concept isn't even in such a person's head. Perhaps this will be solved in time, but we are not there yet, and we're not close.