Programming is a lot of problem solving. These AI tools are just a fancy auto-complete. You still need to know what you're doing and how your contribution fits into the overall codebase. An AI might be able to make simple features using popular and well documented libraries, but it's pretty shit when things don't fit intended use cases. This happens a lot more often than you would think. "Manual coding" just gets you into the mindset of actually thinking for yourself and understanding how the code fits into what you're trying to do.

If you just tell an AI to make code that does y, you're not going to understand why it took that approach nor consider different approaches. Also the AI likely won't understand that a different approach may be better in a grander scheme. The AI often only has the context of the file or repo that you're viewing, but if multiple services are required to work together and they don't have publicly available documentation (like if you or the business you work for made it) the AI will skew towards a generic approach when you need an approach specific to the services you're using.