01
Do not automate the messiest process first.
The process causing the most frustration is not always the best first automation target. If its rules are unstable, ownership is unclear, or every case is an exception, software can make the confusion faster rather than removing it.
The best first target is usually boring: frequent, structured, measurable, and expensive enough to matter.
02
Score the workflow before choosing the technology.
A useful automation candidate usually scores well across five dimensions.
- Volume: it happens often enough to justify the system.
- Rule clarity: the normal path can be described precisely.
- Data readiness: the required information already exists or can be captured reliably.
- Business impact: time, errors, revenue, or response speed can be measured.
- Exception handling: unusual cases can be routed to a person instead of breaking the flow.
03
Automate the decision boundary deliberately.
Not every step should become autonomous. A good system defines which work is deterministic, which work benefits from AI assistance, and which decisions need explicit human approval.
That boundary is architecture, product design, and operational policy at the same time.