Is RPA the same as AI? What’s the Difference, and What Are the Use Cases?
The short answer is: No, robotic process automation (RPA) and artificial intelligence (AI) are not the same thing. However, they are two complementary technologies that can increase efficiency in a wide range of business processes.
If you are currently wondering which one your team needs to boost productivity, reduce costs, or unlock previously unreachable use cases, the following analogy might help: AI is the brain; it aims at mimicking and eventually surpassing human reasoning. RPA is the brawn; it enables automation of human actions.
In other words, if you need to automate simple and repetitive tasks, while bringing high accuracy, reliability and traceability, RPA is your choice. On the other hand, if you need to perform more complex reasoning tasks or extract patterns from unstructured data, then go for AI. Of course, do not hesitate to use both if your business problem requires it.
In this article, we will go through a few use cases. Hopefully by the end of it, you will be better equipped to decide if you need AI, RPA, or both.
RPA: Automating Simple & Repetitive Tasks
RPA uses software robots to automate human actions in business processes that involve interaction with digital systems. These actions are usually simple and repetitive, which makes them prone to human error and can provoke a loss of employees’ motivation and efficiency.
Software robots and RPA on the other hand bring notable benefits: accuracy (by minimizing human error), reliability (by being always available and by reducing delay), traceability (by providing audit trails and logs), and productivity (by increasing processing speed). A few examples of use cases are automating orders, processing payroll, customer onboarding, data validation, etc.
An example of a company providing an RPA software platform is UiPath. Their software integrates both ways with Dataiku DSS, which can bring together the worlds of AI and RPA. More precisely, you can query a Dataiku DSS API node to leverage machine learning models in the UiPath workflows, and import UiPath logs into Dataiku DSS as well as start UiPath Orchestrator processes directly from Dataiku DSS.
Example Use Case: Insurance Claims Processing
Insurance claims processing is crucial to the insurance business, and it is also a typical process that can be automated with RPA. To understand why, let us go through all the steps that a human would perform for a single insurance claim:
- Receive the claim as a PDF in an email.
- Download the PDF to a shared drive in a queue folder.
- Open the oldest claim in the folder.
- Compare it to the company’s data in its internal software.
- If no discrepancies are found, copy the claim data into the internal claims software and attach the PDF.
This can take tens of minutes on average for a human depending on the amount of data to check and the delay between each claim. Also, the process is limited to employee working hours.
In contrast, an RPA robot would perform steps (1) to (4) continuously without human intervention, unless it finds a discrepancy, in which case it would notify the human operator. Finally, the robot would send an automated email using a predefined template to the relevant department for further processing. This can only take a few minutes, is done exactly the same way every time and all day long, while providing an audit trail. Insurance companies can thus save on costs, and improve their efficiency while keeping human intervention for more complex business processes.
This article was originally published by Dataiku, read more.