I think AI will still be important, but the AI of the future won't look like the AI that we have today. People have a tendency to redefine "AI" to mean whatever the new hotness is -- LLMs today, deep neural nets a few years ago -- but new things are created all the time, and fads always change. When I started grad school for comp sci nearly 20 years ago, I worked with a group that was big on "AI", but we were dealing with multi-agent systems. No neural nets or super-intelligences or anything like that. Neural nets were actually considered passé back then; I vividly recall a professor telling me that SVMs (support vector machines) were stronger than neural nets, because SVMs had a stronger theoretical foundation and were more amenable to mathematical analysis. Neural nets, on the other hand, just happen to work -- but they happen to work very very well! Deep learning didn't gain traction until after I had finished grad school.
The LLMs that we have today are amazing, but there is still plenty of room for improvement. Having to train it on a huge dataset is problematic for some uses; perhaps there is a related structure that can be trained more easily and more quickly. That would also reduce the effect of OpenAI's monopoly. LLMs also have specific weaknesses, like poor performance at arithmetic. At this stage, I wouldn't really feel comfortable feeding problems into an LLM and presenting users with the LLM's answers. It's still the Wild West in many aspects. There is always an improvement on the horizon, but it's hard to tell where it will come from and when it will come. Maybe we'll have LLMs that really start to resemble intelligence, or maybe we'll have a totally different structure that does everything LLMs can do plus more.