A decent chunk of the tech community can already run smaller T5 Flan models or the 6B EleutherAI LLM GPT-J (and the likely similarly sized upcoming Open Assistant) on their own machines, at decent inference speed (< 0.2 s per token, which is ok enough most of the time). By 2027 or so the majority of consumers will likely exceed that point.
What happens when models are updated every day automatically and you can run all your search and answer tasks on your local machine?
With GPT-J - which is unreliable and aging now - I can already learn core intro to psychology topics more accurately/faster than with google or wikipedia, and I can do that offline. That's a cherry picked use case, but imagine the future.
Why would you use something that has ads when you can run it locally, and perhaps even augment it with your documents/files?
In the end game this is where Google is in the same place as Kodak in my opinion right now. Sure it's $0.01 or more a search for OpenAI now, but it won't stay that way (they reduced prices by 66% half a year ago), and at that rate you can already make the unit economics work anyhow as a startup.