If they mean "machine learning", then sure there are application in cancer detection and the like, but development there has been moving at a steady pace for decades and has nothing to do with the current hype wave of GenAI, so there's no reason to assume it's suddenly going to go exponential. I used to work in that field and I'm confident it's not going to change overnight: progress there is slow not because of the models, but because data is sparse and noisy, labels are even sparser and noisier, deployment procedures are rigid and legal compliance is a nightmare.
If they mean "generative AI", then how is that supposed to work exactly? Asking LLMs for medical diagnosis is no better than asking "the Internet at large". They only return the most statistically likely output given their training corpus (that corpus being the Internet as a whole), so it's more likely your diagnosis will be based on a random Reddit comment that the LLMs has ingested somewhere, than an actual medical paper.
The only plausible applications I can think of are tasks such as summarizing papers, acting as augmented search engines for datasets and papers, or maybe automating some menial administrative tasks. Useful, for sure, but not revolutionary.