The policy changes by conversation
People resolve the same case differently because the rule itself is unsettled. Automation would make the disagreement faster, not smaller.
A workflow is ready for automation when it has a clear trigger, a visible finish, reliable inputs, explicit decision rules, known exceptions, and an accountable owner. If people still disagree about the policy or reconstruct the work from memory, fix the process before automating it.
Clear answers across all five gates support a bounded pilot.
Software can enforce a known process. It cannot resolve unclear ownership, conflicting policy, or evidence that nobody trusts.
A clear route needs more than repetition. It needs evidence, decision boundaries, exception handling, and ownership.
A specific event starts the work, and the completed result can be observed without interpretation.
The workflow begins whenever someone notices a problem and ends when people stop asking about it.
The operator can name the records, fields, documents, and source systems needed for an ordinary case.
Critical context lives in private messages, personal memory, or documents nobody can locate consistently.
The team can separate deterministic rules from classifications, commercial judgment, and regulated decisions.
Different operators apply different policies, but the organization treats every result as equally correct.
Known exceptions enter a review path with the evidence and owner needed to resolve them.
The proposed system must guess through missing data, conflicting rules, or unusual cases to keep moving.
One role owns the workflow definition, its success measure, and the decision to expand or stop automation.
The software team owns implementation, but nobody owns whether the operating result is correct or useful.
A pause is useful when it prevents a broken rule or unreliable record from becoming a faster source of errors.
People resolve the same case differently because the rule itself is unsettled. Automation would make the disagreement faster, not smaller.
Missing identifiers, duplicate records, and conflicting versions prevent the system from knowing which input should control the result.
The team wants less manual work but cannot state the correct outcome, acceptable exceptions, or evidence needed after each action.
The first version should finish one useful route and make every stop, review, action, and result visible.
Follow completed work, one exception, and one stalled case through the tools and side channels people actually use.
Name states, evidence, permissions, review conditions, failure behavior, and the person accountable for the result.
Start in observation or draft mode. Compare the system with the operator before granting wider authority.
Readiness depends on the operating boundary, not the excitement around a tool or model.
No. Repetition helps, but the task also needs reliable inputs, a clear outcome, and safe handling for exceptions and failures.
Automate only the stable parts. Keep changing policy in a configurable or human controlled layer until the organization understands it.
The system can collect evidence, apply routine checks, prepare a recommendation, and route the final decision to an authorized person.
No. You need enough reliable data to support one bounded path and a clear response when required evidence is missing or contradictory.
Choose one frequent workflow with a visible start, a checkable result, a known owner, and enough examples to test ordinary and exceptional cases.
Share its trigger, owner, evidence, decisions, exceptions, and required result. That is enough to start a useful diagnosis.