Not everything needs AI. Some work is better with simple rules. Here's how to choose.
The Decision Framework
Match the technology to the shape of the work:
| Work Shape | Best Technology |
|---|---|
| Repeatable, consistent inputs | Rules-based automation |
| Variable but bounded | AI agents |
| Dynamic, goal-driven | Agentic AI with governance |
When Rules-Based Automation Wins
Use traditional automation when:
- Clear if-then logic: When X happens, do Y
- Consistent inputs: Same format every time
- Predictable outputs: Always produces same result
- No judgment needed: Binary decisions
- Speed matters: Rules execute faster than AI
- Low cost priority: No AI API costs
Example: "If order > $100, apply free shipping" — Pure rule, no AI needed.
When AI Adds Value
Use AI when:
- Judgment required: Context changes the answer
- Variable inputs: Different formats, unstructured data
- Edge cases common: Rules would need endless exceptions
- Nuance matters: Subtle differences in meaning
- Natural language: Understanding human communication
Example: "Classify this customer email" — AI understands intent, sentiment, urgency better than rules.
When Agentic AI Makes Sense
Use agentic AI when:
- Multi-step workflows: Several actions needed
- Goal-oriented: Working toward an outcome, not a task
- Cross-system: Multiple tools and databases
- Dynamic adaptation: Next step depends on previous results
- Planning required: AI figures out the steps
Example: "Handle this customer issue" — AI researches, emails, creates ticket, escalates if needed.
Comparison Table
| Factor | Rules | AI | Agentic AI |
|---|---|---|---|
| Setup complexity | Low | Medium | High |
| Ongoing cost | Low | Medium | High |
| Flexibility | Low | Medium | High |
| Speed | Fast | Medium | Slower |
| Explainability | High | Low | Low |
| Error handling | Predictable | Variable | Complex |
The Hybrid Approach
Most real workflows combine all three:
- Rules: Route incoming requests
- AI: Classify and understand request
- Agentic AI: Handle complex cases end-to-end
- Rules: Apply business logic (discounts, approvals)
Common Mistakes
- Using AI for simple rules: Over-engineering
- Using rules for complex judgment: Brittle system
- Using agentic AI for single tasks: Unnecessary complexity
- Not testing rules exhaustively: Edge cases break
- Not monitoring AI: Silent failures
Questions to Ask
Before choosing AI:
- Can I write explicit rules for this?
- Do inputs vary significantly?
- Does context change the answer?
- Is judgment actually needed?
- What happens if AI gets it wrong?
If rules work, use rules. If not, then AI.
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