Traditional automation is best when the correct rule can be written and tested. AI can help when the difficult part is understanding varied language, documents or conversation.
Key takeaways
- Use ordinary rules wherever the correct answer can be written down.
- Give AI one interpretation task and test its quality.
- Require a person to review actions that could affect money, access or customer relationships.
Use ordinary rules when the answer is known
Keep calculations, validation, permissions and known routing rules in ordinary software. They are cheaper to test and easier to explain.
Use AI for varied language and documents
AI may help with classification, summaries, information extraction, translation and conversational input when the wording or structure changes from case to case.
Combine AI, rules and people
AI can interpret a request, ordinary software can check the result and a person can review an action that affects money, access or a customer relationship.
Test how the system fails
Use real ordinary, difficult and unacceptable examples, name the errors that cannot pass and keep checking quality after launch. A polished demo does not show how the workflow will behave every day.
Use the simplest technology that can do the job
A practical design often combines methods: AI interprets varied language, ordinary software checks the result and a person handles sensitive or unclear cases.
| Decision area | Useful evidence | Warning sign |
|---|---|---|
| Input | Structured values and known states | Free-form language, documents or variable phrasing |
| Correctness | The rule can be written and tested directly | Quality must be checked against real examples |
| Consequence | A failed action is contained and reversible | An error affects rights, money, safety or an important relationship |
| Review | Logs and the person handling exceptions are named | The model acts without a review or escalation path |
Example: interpret the request, then use rules to act
AI may classify an inbound message and extract a requested date. Ordinary software should still confirm that the customer, permission and date are valid. If the answer is unclear or the action matters, the request moves to a person with the original message and proposed interpretation attached.
Apply this to your software project
Bring one example of the workflow, the people involved, the bottleneck you see most often and what should improve. You do not need a finished specification.
For help with this decision, see AI integrations and agents for defined business workflows.
Sources and further reading
- NIST AI Risk Management FrameworkA practical framework for governing and monitoring AI risk.