Automation is usually discussed as a capability question. It is a readiness question. Here are the tests.
The five tests for ready
1. It is written down. Not described in a meeting. Written, in steps, with the decision points named. If two people write different versions, you have found something more valuable than an automation opportunity.
2. It happens often enough. A useful floor is around twenty times a month. Below that, the build plus maintenance usually costs more than the hours returned. The exception is anything where a human error is expensive rather than annoying.
3. The inputs are consistent. Same fields, same shape, same meaning. Where they are not, you need an explicit rule for the exceptions before you build, not after.
4. The outcome is checkable. You can open a record and see whether the right thing happened. A green execution log is not proof. If nobody can verify the result in the system of record, you will not know when it breaks.
5. Failure is recoverable. If a step fails, you can retry or undo it. Where you cannot, that step needs a human checkpoint.
The three reasons to wait
The process is still in debate. Automating a disagreement encodes one side of it in software and turns every future discussion into a change request.
The data cannot be trusted. Automation applies bad data faster. Fix the inputs first, or route the unusable records into a flagged path rather than processing them.
The step is irreversible and nobody approves it. Sending money, deleting records, messaging a customer at scale. The rule that holds up: automate up to the irreversible action, put a human checkpoint there with enough context to decide in seconds, and automate everything after.
Start smaller than feels satisfying
The guidance from people who build these systems is consistent: begin with the simplest thing that works and add autonomy only where it earns its cost. In practice that means automating one step, watching it for a week, then extending.
The opposite approach, building the whole flow and switching it on, is how teams end up debugging five things at once with no idea which one is wrong.
The question that saves the most money
Ask what happens if this runs wrong for a week before anyone notices.
If the answer is tolerable, build it. If the answer is expensive, build the alerting first and the automation second. And if the answer is that nobody would notice, you have discovered that the process may not need to exist at all, which is the cheapest outcome available.