Cognitive Automation
Completes processes that normally require human intervention by engaging decision-making mechanisms through adopting a knowledge-based approach.
Cognitive Automation constitutes the biggest expense item in AI world thanks to its ability of learning the most similar behavior to humans. It can perform more complex operations than Robotic Process Automation processes that apply repetitive behaviors through an interface.
The fundamental difference of Cognitive Automation and Robotics Process Automation, which is based on rules and if-then principles, is that the former knowledge-based and the latter is process-based.
Cognitive Automation that progresses by interpreting data, also follows a different way in terms of data processing. Since RPA uses only structured or semi-structured data, can be thought of as a data operator. However, Cognitive Automation can identify patterns, while processing unstructured data.
Robotic Process Automation is more suitable for processes that contain strictly rule-based and structured, and large amounts of data. However, the use of Cognitive Automation should be preferred for complex, unstructured data that requires human intervention.
The structural difference allows Cognitive Automation to take part in more critical tasks as well. In addition to the tasks such as fraud detection and market forecast, it is also possible to create a customer support team from Cognitive Automation bots or create a forecast engine that gives customers fast feedback through the system.
Differences between Robotic Process Automation and Cognitive Automation
| RPA | Cognitive Automation |
|---|---|
| Repetitive and rule-based processes | Non-routine tasks that require human decision |
| Low cost and high-quality | Added value services |
| Extended scope of use | Limited scope of use |
| Can use structured or semi-structured data | Can use structured, semi-structured or unstructured data |