With AI, there's a qualitative difference. We know exactly how the AI is built, but we have no idea what the Gigabytes of FP32 numbers that make up the weight tensors actually encode. We can actually ask the AI to "find the optimal structure of a protein" without knowing how it finds the optimal. Currently, it requires a lot of massaging of data and cajoling the weight tensors to be "just right" in order to get good answers, but in the future we can imagine AI giving very good answers that are "out of our league" (in terms of understanding as to how or why) that are nonetheless optimal according to some metric we can measure.
The work itself can be fairly mechanized. Even when it isn't, most of it is often done by an army of techs and grad students, rather than the nominal "prize winner".
Now, an AI that undertook an independent program of research - that would obviously be different.