That seems rather risky, considering that they don't really check that they output accurate information, and OpenAI specifically recommends against using it for that due to the possibility of their GPT models outputting falsehoods as fact.
If you're double-checking the sources, both to make sure that they exist, and they are accurate, you may as well do the research without using an LLM in the first place.
You're just adding to your workload unnecessarily in that case.
That’s not necessarily true, LLMs are a very useful research aid because they give you a place to start. They give you a high level summary and may cite sources which may/may not exist, and it’s up to you to fact check and develop your own opinions. They can also summarize complex texts and filter out SEO garbage that would otherwise clutter google search results. Research still works the same as before, LLMs are just an accelerator if used correctly.
The issue with LLMs that I have is that while they are great at certain tasks, they are bad at anything, let's call it factual, due to their nature.
I can for example use it to quickly draft up a email or a piece of python code, and I can immediately see whether or not the response it generated is actually what I want.
If I go ask it what the hottest day in a given country was or ask it to explain something, I have absolutely no idea whether it's bullshit or not and I will have to double check it anways.
I think the learning curve with LLMs as a tool is to be able to know when to use it and when to rely on other sources instead.