Traditional automation is preferable when a rule can be written and verified. AI is useful where language, ambiguity or pattern interpretation matters and errors can be contained.
Use rules for certainty
Calculations, validation, permissions and known routing rules should remain deterministic. They are cheaper to test and easier to explain.
Use AI for interpretation
Classification, summarization, extraction, translation and conversational input may benefit from models when inputs vary in language and structure.
Combine the two
A strong workflow can use AI to interpret a request, ordinary software to validate it and a person to approve a high-impact action.
Evaluate real failure cases
Build a representative test set, define unacceptable errors and monitor production drift. A convincing demo does not establish operational reliability.
A practical checklist
- Name the outcome in plain language.
- Map the current people, responsibilities and exceptions.
- Separate evidence from assumptions.
- Make ownership, cost and operating risk visible.
- Choose the smallest next step that reduces a material unknown.
What to bring to a first discussion
Bring one real example of the workflow, the people involved, the constraint you feel most often and what a useful outcome would change. You do not need a finished specification.
For direct help with this decision, see Applied AI connected to a useful business workflow.