Five years ago, the news media was convinced that "3D printing" was going to revolutionize manufacturing. For those of us who have been using rapid prototyping for a couple decades, that seemed rash. It was. Desktop 3D printing at consumer cost points is a thing now, yes, but for manufacturing the materials are the limitation and progress remains slow and steady.
Likewise with AI. It will probably overhaul low-grade marketing and copywriting content, but where accuracy (and liability) is paramount, I do not think it will change much. Like any automated tools we already have, you can just generate more junk that needs to be manually edited to remove the errors and oversights.
Another goodie is a 'digital twin'. I think most of us have fantasized about analytical methods that include 'everything' about a real system. Make up a pretty name that implies an unrealistically simple image of a wildly (impossibly) complicated reality, and you make money.
What I've already seen is the increasing gap between management expectations and actual engineering reality. It will continue to be more difficult for high-value 'Real Engineers' doing 'Real Engineering' when corporate is being buzz-washed about how the next new software tool will do it all for you, for so much less. Business plans that underbudget the technical cost or overlook technical problems that need solutions might still call in the engineers to solve the problems, but that's not a sustainable employment path for entry-level and stability-seeking engineers. So there will be even more churn, panic, and turnover as companies experiment with more reliance on the tools and then either failing or calling in actual engineers to solve the problems that the automated / AI tools simply can't resolve.
If I could imbue any skill on tomorrow's engineers, it's to study and verify the results of the tools they will increasingly rely upon.