AI is most valuable when it improves a workflow the team already understands. Starting with the model instead of the operational problem often creates an impressive demo that is difficult to trust or maintain.
Look for structured repetition
Strong candidates have a recognizable input, a repeatable decision, and a useful output. Lead enrichment, support triage, content classification, and document extraction often fit this pattern.
- The input can be validated before processing.
- The output has a clear destination and owner.
- A human can review uncertain or high-impact cases.
Keep the workflow observable
An automation should show what happened, what data was used, and where the result went. Logs, retry rules, cost limits, and explicit failure states are part of the product—not optional infrastructure details.
AIAutomationWorkflows