Operations · 5 min
RPA and AI: which processes to automate with what
RPA and AI are two complementary approaches to automation. RPA (Robotic Process Automation) carries out repetitive tasks by following fixed rules; AI handles situations that require understanding, judgement or language. Knowing when to use one, the other or both is the key to automating effectively.
Key points
- RPA automates repetitive tasks based on fixed rules.
- AI handles language, variable documents and decisions.
- RPA is fast but rigid; AI is flexible but requires data and controls.
- Combining them automates complex end-to-end processes.
RPA: ideal for fixed rules
RPA excels where the process is stable, predictable and based on clear rules: copying data between systems, filling in forms, running steps that are always the same. It is quick to implement and reliable, but rigid: if the process changes or presents exceptions, it has to be reconfigured.
AI: needed for understanding and variability
AI comes into play when interpretation is needed: reading non-standard documents, understanding language, classifying, deciding between options. It handles the variability that would throw a pure RPA into crisis, but it requires adequate data and controls.
- RPA: stable processes, fixed rules, structured data.
- AI: language, variable documents, classification, judgement.
- RPA + AI: RPA executes, AI interprets the complex parts.
Combining them: the best of both worlds
The best results often come from combining them: AI interprets and decides on the complex steps, RPA carries out the repetitive operations on the systems. Together they automate processes that neither could handle on its own.
FAQ
Do I have to choose between RPA and AI? +
Not necessarily. Often the best solution combines them: RPA for the repetitive operations, AI for the parts that require understanding or judgement.
Is RPA obsolete compared to AI? +
No. For stable, regular processes it remains efficient and reliable. AI complements it where flexibility is needed; it does not replace it everywhere.
Which one should I start using? +
It depends on the process: if it is stable and rule-based, RPA delivers value immediately; if it requires interpreting text or deciding, you need AI.
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