Use rules when the rules are enough
Traditional automation is ideal when inputs are structured and decisions are deterministic. Validation, calculations, notifications, field mapping, and system synchronization are often safer and less expensive as ordinary code.
Adding a language model to a deterministic task can increase cost and variability without improving the result.
Use an AI agent for bounded interpretation
AI agents become useful when work requires interpreting unstructured text, comparing evidence, drafting a response, or choosing among permitted tools. They should still operate inside explicit boundaries for data, actions, time, retries, and spend.
- Classifying varied documents or messages
- Summarizing evidence with citations
- Drafting context-specific communications
- Proposing next steps for human approval
- Finding conflicts or missing information
Choose a hybrid design
Many reliable systems combine both approaches: deterministic code gathers and validates inputs, an AI model performs a bounded reasoning step, and rules enforce permissions and route the output for review.
The right question is not whether a process should use AI. It is which parts require interpretation, which parts require certainty, and where a person remains accountable.