Responsible choices
When is regular automation better than AI?
AI is valuable when inputs vary or meaning must be interpreted. It is often unnecessary when the process follows stable rules and structured data.
Calculations, validations and fixed routing rules are cheaper, easier to test and more predictable in regular software. Adding AI to these steps can introduce uncertainty without adding value.
Documents with changing layouts, free-text email and questions across large knowledge collections are examples where language models or document AI can help. Their output should still enter a controlled workflow.
The strongest solutions often use AI to interpret an input, regular software to enforce rules and a person to decide on sensitive exceptions.
- AI interprets variable information
- Rules validate and constrain
- Integrations move approved data
- People handle responsibility and exceptions