Intelligent Process Automation (IPA) vs. Robotic Process Automation (RPA)

[Aklima@416]

As technology evolves, you’ll hear more and more about robotic process automation (RPA) and intelligent process automation (IPA) . But what do these two concepts mean? Simply put, robotic process automation (RPA) can be compared to the diligent worker who automates repetitive tasks. In contrast, intelligent process automation (IPA) turns that work into an orchestra, adding cognitive notes and AI harmonies.

Just as a conductor shapes the performance of an ensemble, we'll help you determine which automation symphony best fits your organizational goals.

What is Robotic Process Automation (RPA)?
Robotic process automation uses technology to mimic human tasks to complete a business process. RPA robots mimic computer tasks that are repetitive, rule-based, have defined inputs and outputs, are repeatable, and occur frequently.

Robotic process automation uses structured data to complete tasks. Data entry, data processing and matching, customer onboarding, and opening new accounts are examples of tasks where RPA technology works well.

Illustration of a brain neural network representing robotic process automation



RPA and artificial intelligence (AI) are distinct concepts , even though they are confused . Although some argue that RPA can be considered an artificial intelligence technology, the two technologies are distinct.

Unlike AI, RPA robots typically cannot learn. RPA typically struggles to adapt to change. Rather than solving the problem independently, RPA strives to adapt to changes. While RPA is designed to mimic human actions, AI simulates how humans think.

What is Intelligent Process Automation (IPA)?
Intelligent process automation builds on RPA and numbers in finnish encompasses it with artificial intelligence. IPA mimics human actions and can learn to improve them over time. IPA typically consists of four core technologies:

Machine learning
Natural Language Processing (NLP)
Intelligent workflows
RPA
We've already covered the APR above; let's briefly look at the other three...

Components of Intelligent Process Automation: Machine Learning, Natural Language Processing, and Intelligent Workflows

Machine learning
Machine learning is an application of artificial intelligence that allows systems to access data and learn without being programmed. Machine learning uses supervised or unsupervised algorithms to identify patterns in structured data.

Supervised algorithms create inputs and outputs before making their own predictions. Unsupervised algorithms observe structured data and develop insights from pattern recognition.

Combined with RPA, bots can assess their effectiveness and make adjustments to improve processes. With deep learning , systems can use data collected in one context to improve others.