That should be quite easy compared to software development, which is much more open-ended since the requirement are usually more nebulous, potentially contradictory, and at times simply wrong.
SysAdmin stuff is quite easy in terms of complexity to some sw stuff. The problems, similar to traditional engineering, tend to come from the rather high cost of failure.
To expand further, it's easy to setup a system but hard to setup one that's reliable and/ or resilient. It's hard to maintain systems that are not documented and/ or wrongly documented (outdated, inaccurate). It's even harder to always make sure everything's consistent and you don't lose/ damage data.
Yeah imagine giving an AI root access to the server with your production database on it. Now I really want to try that in a VM to see what will happen. Even odds at some point it tries to rm-rf everything.
Nobody is considering giving AI unrestricted access to anything yet. Code written by AI is reviewed by humans, and I would be shocked to hear that sysadmins are considering letting AI agents execute arbitrary commands.
Yet, I haven't seen an AI that solves the software distribution problem. Tools like ChatGPT are often plain wrong when answering questions about basic sysadmin problems, and even make up commands.
The software distribution problem is not a close-ended, technical task that we could realistically expect an LLM to have an answer for. At least not now. The latter problem could eventually be lessened by fine-tuning the LLM more specifically and by improving the tooling around it. For example, by automatically briefing it about peculiarities of the operating systems.
ChatGPT-4 is wonderful for composing regular expressions. Saves so much time when transforming various Java strings that arise in my work.
Today's big time savings came from this prompt:
"Write a Java method that uses the Eclipse AST parser to create a simple markdown file showing the commented method signatures of a given Java class text file."