Write down the trigger and the finish line
State exactly what starts the workflow and what successful completion means. If the start or end cannot be described clearly, the process may not be stable enough to automate yet.
List every system and data field
Identify where information comes from, where it must go, who owns each system and which fields are required. This exposes missing APIs, permissions and data-quality issues before development.
Capture exceptions
Ask what happens when information is missing, duplicated, late, contradictory or sensitive. Decide which exceptions can be handled by deterministic rules and which need a human decision.
Define permissions and approvals
Use the minimum access required. High-consequence actions such as payments, account changes, legal commitments or sensitive customer decisions should have explicit human review where appropriate.
Design the failure path
Logs, alerts, retries, duplicate protection and a manual takeover path are production requirements. The automation should fail visibly and safely rather than silently.
Questions businesses ask
01Do I need AI for business automation?+
No. Many valuable workflows are better handled with deterministic rules. AI is useful when the task involves language or uncertainty and appropriate oversight is possible.
02What information should I collect before an automation project?+
Document the trigger, systems, inputs, outputs, owners, exceptions, permissions, approvals, expected volume and cost of failure.
03How do I know whether an automation is working?+
Define measurable outcomes such as reduced handling time, fewer errors, faster response or improved completion rate, then monitor failures as well as successes.
