The guide
Where AI helps in research writing, and where it does not
AI writing tools are good at some parts of research writing and risky at others. Knowing which is which keeps your work fast and trustworthy.
Sources and references
Finding candidate papers, keeping references in order and formatting them are slow, mechanical jobs. Tools help most here, as long as every citation points to a real record you can open.
The risk is the opposite case: a model writing citations from memory. Those can look plausible and not exist, which is why citations should come from a catalogue or your own library.
Drafting from your outline
A first draft that follows your outline and section prompts can save time, especially for methods and background. It is a starting point, not finished text.
What a model cannot know is what your data show and what they mean. Results and interpretation are yours to write, and every suggested sentence is yours to check.
A second reader before submission
An AI reviewer can point out unclear arguments, missing limits and questions a referee is likely to ask, quickly and at any hour.
It does not replace your co-authors or the journal's reviewers. Use it to fix the obvious problems first, so human readers can spend their time on the hard ones.