RPA vs AI automation
RPA is useful for deterministic UI or system steps. AI automation is useful when documents, language, classification, summarization, or exception handling are involved.
How to choose
Choose the simplest reliable tool for the job. Many good workflows combine deterministic automation with AI-assisted steps.
- RPA for repeatable clicks
- APIs for reliable integration
- AI for language and uncertainty
- Human review for risk
Where RPA fits
RPA is a good fit when the workflow is stable, rule-based, and mostly repeats the same interface steps without much interpretation.
- Stable screens
- Known fields
- Low exception rate
- Clear rollback path
Where AI automation fits
AI is useful when the workflow depends on reading, classifying, summarizing, extracting, or proposing a decision from messy inputs.
- Emails and tickets
- PDFs and forms
- Natural-language search
- Review queues
- Draft recommendations
When to build software instead
If the workflow needs permissions, audit logs, user review, dashboards, APIs, or ownership, a custom app around the automation is usually safer than more scripts.
- Role-based access
- Audit trail
- Editable AI output
- API integration
- Operational dashboard
Preguntas frecuentes
- What is the difference between RPA and AI automation?
- RPA follows deterministic rules and interface steps. AI automation handles language, documents, classification, summarization, and uncertain inputs.
- Should RPA be replaced by AI?
- Not always. Stable rule-based steps can stay in RPA. AI should be added where interpretation, extraction, or review is needed.
- When should we build custom software?
- Build custom software when the automation needs UX, permissions, audit logs, API integration, human review, or long-term ownership.