RPA and AI: Who Does What Between Rules, Models, and Humans
Duration 2:52
Intelligent automation isn't "AI that does everything." It's a precise division of labor: rules handle the certain, models handle the probable, and people handle the difficult. We break down how it actually works — the confidence threshold, escalation to a human, and the human decision that retrains the model. Plus the platforms that brought it into the mainstream and what it means for a business.
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Transcript
We often set humans against machines. The real question lies elsewhere. In a process, who does what between the rule, the model and the person? RPA, or Robotic Process Automation, handles repetitive, rule-based tasks. It opens a document, extracts the fields, files them. Always the same way. But RPA decides nothing. It runs a rule written in advance. The moment a case falls outside the rule, it stops. That is where AI comes in. Artificial intelligence, for its part, mimics human judgment. It learns, reasons, perceives. Faced with a new case, it classifies, it connects, it proposes an answer. But the model does not always decide alone. Every answer carries a confidence level. If that confidence is high enough, the case goes through without anyone. If confidence is too low, the case moves up to a person. The machine never forces an uncertain decision. It knows when to hand over. This human decision is not lost: it feeds the model. The next case, the AI will handle with more assurance. The system learns from its own limits. Here is the real pattern. The rule takes the certain. The model takes the probable. The person takes the difficult. None of the three replaces the others. This mechanism is being industrialized. Platforms like UiPath, Automation Anywhere or Microsoft Power Automate have spread it across companies. SS&C Blue Prism follows the same path. In 2025, these tools are no longer a promise. They already run in back-offices. Processing gains speed, data-entry errors decline. But nothing comes for free. A poorly trained model reproduces bias. Sensitive data calls for strict safeguards. And teams must learn new practices. Work shifts, it does not disappear. Routine tasks move to the machines. Analysis and customer relations gain weight. At Koaee, we apply this division to customer relations. Our assistants handle the repetitive exchanges with our clients' customers. A sensitive case moves up to a person. This film only skims the surface; the full article is in the comments, below the video. To follow artificial intelligence more broadly, subscribe. A like helps us. See you soon on koaee.ai.