As far as I know, AI is Software, so this type of reasoning really confuses me.
I think it is possible that "developers" might have some of their work find automation using AI and ML, but Computer Science will obviously stick around as long as computers are around.
For example, someone has to code the algorithms which are used to teach the computer how to learn. Someone has to code the pipelines for capturing data from the physical world into the digital world. Someone has to code the storage and exchange of that data to the ML models, and someone has to plug the inference into the production processes and systems. Someone has to put alarms and monitors around all these things to assert their operation. Someone has to code the UIs and interfaces that users will use to interact with all those systems. Finally, someone needs to code compatibility and optimizations of all these models and their implementation to continue to work and leverage new hardware capabilities.
If people think that developers were spending 90% of their time hand tuning business rules and coming up with manually implemented inference and decision models they are highly mistaken. That could have been 5% of the job in some circles, but 95% of the job has always been all these peripheral tasks.
If anything, there will be even more work now, since ML models require a lot more periphery to develop, train and ship.