“Should we use RPA or AI?” is one of the most common questions I get from Swiss businesses exploring automation. The answer, as with most technology decisions, is “it depends.” Let’s break down when each approach makes sense.
Understanding the Fundamentals
What is RPA?
Robotic Process Automation (RPA) uses software “bots” to mimic human interactions with computer systems:
- Clicking buttons
- Copying and pasting data
- Filling forms
- Moving files
- Sending emails
Key characteristic: RPA follows explicit rules. If A happens, do B. It doesn’t “think”—it executes predefined steps.
What is AI Automation?
AI automation uses machine learning and large language models (like Claude) to:
- Understand natural language
- Make decisions based on patterns
- Handle unstructured data
- Learn from examples
- Generate content
Key characteristic: AI can handle ambiguity and variability. It interprets intent, not just instructions.
When to Use RPA
RPA excels in scenarios with these characteristics:
High Volume, Consistent Processes
If you process 1,000 invoices per month and they all follow the same format, RPA is perfect. The bot can:
- Log into your accounting system
- Navigate to the invoice entry screen
- Enter data from standardized documents
- Submit and move to the next
Stable Systems and Processes
RPA bots interact with screens. If your software changes its interface, the bot breaks. Use RPA when:
- Systems are stable (not frequently updated)
- Processes rarely change
- User interfaces are consistent
Rule-Based Decision Making
When decisions follow explicit rules without exceptions:
- If invoice < CHF 1,000, auto-approve
- If customer tier = Gold, apply 10% discount
- If payment is overdue > 30 days, send reminder
No Interpretation Required
RPA works best when data is structured and meaning is obvious:
- Copy field A to field B
- Add column C to column D
- If status = “Complete”, move to folder X
When to Use AI
AI shines in different scenarios:
Unstructured Data
When information doesn’t come in neat formats:
- Emails: Understanding requests, sentiment, urgency
- Documents: Contracts, reports, PDFs without standard layouts
- Conversations: Chat messages, meeting transcripts
Variable Processes
When the “how” changes even if the “what” stays constant:
- Customer inquiries (infinite variations)
- Document analysis (different formats, languages)
- Quality assessment (subjective judgment)
Content Generation
When you need to create rather than just move data:
- Draft responses
- Write reports
- Summarize documents
- Translate content
Complex Decision Making
When decisions require weighing multiple factors:
- Prioritizing support tickets
- Recommending next actions
- Identifying anomalies
- Assessing risk
The Comparison Matrix
| Criteria | RPA | AI |
|---|---|---|
| Setup complexity | Medium | Medium-High |
| Maintenance needs | High (UI changes break bots) | Medium (periodic retraining) |
| Handling exceptions | Poor (fails on unexpected) | Good (can adapt) |
| Structured data | Excellent | Good |
| Unstructured data | Poor | Excellent |
| Decision making | Rule-based only | Pattern-based, contextual |
| Content creation | None | Excellent |
| Cost per transaction | Very low | Low-Medium |
| Initial investment | Medium | Medium-High |
| Scalability | Linear (more bots) | Efficient (single model) |
The Hybrid Approach
The most successful automations often combine both:
Example: Invoice Processing
- AI Stage: Extract data from invoices (any format, any language)
- RPA Stage: Enter extracted data into accounting system
- AI Stage: Identify anomalies requiring human review
- RPA Stage: Route flagged invoices to appropriate reviewer
Example: Customer Support
- AI Stage: Understand customer query, determine intent
- RPA Stage: Look up customer history in CRM
- AI Stage: Draft appropriate response
- RPA Stage: Update ticket status, log interaction
Real-World Decision Framework
Ask these questions to determine your approach:
1. What’s the data like?
- Structured (forms, databases, Excel) → RPA or AI
- Unstructured (emails, documents, images) → AI
2. How variable is the process?
- Highly consistent → RPA
- Variable but predictable patterns → AI
- Completely unpredictable → Human (with AI assist)
3. What happens when it fails?
- Minor inconvenience → Either approach
- Significant business impact → AI (more resilient) or Human oversight
4. How often do systems change?
- Rarely (< 2x/year) → RPA is fine
- Frequently → AI is more maintainable
5. Do you need content creation?
- Yes → AI required
- No → Either approach
The Swiss SME Reality
For most Swiss SMEs, here’s my recommendation:
Start with AI for:
- Email handling
- Document analysis
- Report generation
- Customer communication
Use RPA for:
- System integrations (when APIs aren’t available)
- High-volume data entry
- Legacy system automation
- Scheduled batch processes
Use Human + AI for:
- Client advisory
- Complex negotiations
- Strategic decisions
- Relationship management
Cost Considerations
RPA Costs
- Tools: UiPath, Blue Prism, Power Automate (CHF 500-2,000/month)
- Development: CHF 1,000-3,000 per bot
- Maintenance: 15-25% of development cost annually
AI Costs
- API usage: CHF 0.01-0.10 per 1,000 words processed
- Development: CHF 2,000-5,000 per workflow
- Maintenance: 10-15% of development cost annually
Hybrid Considerations
- Higher initial setup cost
- Lower long-term maintenance
- Better reliability and flexibility
- Optimal for complex processes
The Future is Collaborative
The distinction between RPA and AI is blurring. Modern platforms increasingly combine both:
- Microsoft Power Automate: RPA flows with AI Builder
- UiPath: Adding AI capabilities to traditional RPA
- Claude + Custom Scripts: AI reasoning with programmatic execution
The winning strategy isn’t choosing one over the other—it’s understanding which tool to apply where.
Getting Started
My recommendation for Swiss businesses new to automation:
- Start with AI for a communication workflow (email, reports)
- Measure results over 4-6 weeks
- Add RPA for system integration needs
- Iterate based on what you learn
The key is starting somewhere. Analysis paralysis is the biggest barrier to automation success.
Ready to determine the right automation mix for your business? Let’s analyze your processes together.
Emanuel Flury helps Swiss SMEs navigate the automation landscape, implementing practical solutions that combine AI and traditional automation for maximum business impact.