>but alone for every researcher who needs to write code for their research, AI can make them already a lot more efficient.

scientists don't need to be efficient, they need to be correct. Software bugs were already a huge cause of scientific error, and responsible for lack of reproducibility, see for example cases like this (https://www.vice.com/en/article/a-code-glitch-may-have-cause...)

Programming in research environments is done with some notoriously questionably variation in quality, as is the case for the industry to be fair, but in research minor errors can ruin results of entire studies. People are fed up and come to much harsher judgements on AI because in an environment like a lab you cannot write software with the attitude of an impressionist painter or the AI equivalent, you need to actually know what you're typing.

AI can make you more efficient if you don't care if you're right, which is maybe cool if you're generating images for your summer beach volleyball event, but it's a disastrous idea if you're writing code in a scientific environment.