Automation is a decision problem, not a labour problem
The question is not which tasks a model can perform. It is which decisions your organisation is willing to delegate, and what happens when one of them is wrong.
Automation projects are usually scoped as labour reduction: find the repetitive task, remove the human. That framing produces systems that are impressive in a demo and untrusted in production.
A more useful frame is decision delegation. Every automated step is a decision the organisation has handed to software. So the design questions become: what is the cost of a wrong decision, how quickly is a wrong decision detected, and how is it reversed?
In practice this means three things. Automate the decisions where the cost of error is low and reversal is cheap. Route the rest to humans as exceptions, with the model's reasoning attached. And log every automated action so that a wrong decision can be found and undone rather than discovered in an audit.
Teams that build this way end up automating more, not less — because each expansion of scope is backed by evidence from the previous one.
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