Not OP, for me the issue is nuance of all of your infrastructure, application and outside layers. There's a lot of documentation and such, but often times things don't work as expected to a degree and it requires filling in the blanks correctly. The amount of times I've had an AI Agent misinterpret an alert and assume it was XYZ when it was some random layer it had no idea about is often.
It can certainly get closer but unless your tech stack is a webserver and an application it can get complicated.
From what I've seen the more complicated the deployment and the more tedious the investigation the more useful the automation is. The agent shouldn't be interpreting the alert much beyond gathering symptoms and identifiers for drilling down into all the underlying data and code. The security side of this is very tricky because the speed that makes the tooling useful also makes it hard to supervise.