Intelligent automation using robots with brains

Intelligent automation

What do you feel after hearing robots with brains? With the latest RPA tools capability evolution, now it is possible to implement RPA solutions with cognitive capabilities. Intelligent automation with software robotics is defining new rules for organizational agility and business execution. Seeking faster, more and most often with few personnel enterprises are prioritizing technology investments that have the ability to speed to empower workers and time to market to make better, strategic and informed decisions as well as to decrease overhead. Well, here is some information related to intelligent process automation using robots which must be better for you to know.

What is RPA?

RPA or Robotic Process Automation is a technology which can allow you to configure robot or a computer program to integrate and emulate the actions of human beings interacting with effective digital systems to execute processes of a business effectively. RPA robots use a user interface to capture information and manipulate applications similar to humans. They interpret data, trigger responses and communicate with the systems to perform an amazing range of repetitive tasks.

Read more about Robotic Process Automation(RPA)

What are RPA tools?

RPA tools are several applications that can provide organizations and businesses with the help of an agile digital workforce. There are various popular RPA tools are available in the market. Selection of an effective RPA tool must be based on the following parameters:

Read more about RPA tools.

What is Machine Learning and Artificial Intelligence?

Machine learning and Artificial Intelligence are two different terms. To understand each of these in the best possible way, have a look at the following information regarding these.

Machine learning

Machine learning is a process of learning in which a machine can learn on its own from past experiences without being programmed explicitly. Machine Learning is an application of Artificial Intelligence which has the ability to learn from its previous experiences automatically to get improvements.

Artificial Intelligence

Artificial Intelligence is a study of how to train computers and make them able to do the things which humans are doing at present. AI is being implemented in the systems to let them behave like humans.

What are cognitive capabilities like a human?

Cognitive capabilities are skills that are brain-based and helping to carry out all the tasks which can be ranged from simplest to the complex ones. These skills have more to do with various mechanisms such as how to learn, memorize, pay attention or find an effective solution for a problem. Commonly these capabilities include learning, thinking and much more than these.

What RPA tools have cognitive capabilities like AI and ML

RPA tools are developing with time and getting cognitive capabilities like Artificial Intelligence and Machine Learning. Some of these applications or ML with RPA are BluePrism, Automation Anywhere, Workfusion, UiPath, etc.

What did already implement with ML with RPA?

RPA is including various RPA companies that are organizing various applications to achieve artificial intelligence and machine learning. Various processes have been implemented with ML with RPA. Most of the solutions are related to information extraction and classification. Some examples you can easily find in almost every industry including:

  • Application processing
  • Procure-to-pay
  • Quote-to-cash
  • Data migration and entry
  • Periodic report preparation
  • Periodic Report dissemination
  • Spam email or SMS classification
  • Sanction screening
  • Dispute email classification
  • Margin call classification
  • Information extraction using unstructured documents

Future Practical Scenarios to use ML for RPA

A combination of RPA and machine learning can help in the reduction of limitations of RPAs because these systems will become able to learn knowledge from their previous experiences. As machine learning is developed technology has become mature already. With the combination of ML and RPA, it will become easier to develop more intelligent systems to solve real-life problems in the best possible way.

Health care industries

RPA can use for analyzing diseases like diabetes based on the person’s information.

Banking sectors

RPA bots are well in identifying Margin calls in banking systems. Also, it can be used for sanction screening process automation.
Identify the possibility to obtain loan for their clients.

Insurance sector

Identify the person is suitable for their health care plan and suggest the best plan to them based on their information

Spam and intrusions detection

Classification of email or SMS whether they are spam or not.

Intelligent resource allocation

Allocating the resources for off-peak times is kind of wasting the resources. RPA robots with cognitive capabilities can detect the best peak time and allocate the resources without wasting them.

Transportation

Setting up the transportation schedules to align with actual passenger needs

Benefits of RPA with Machine Learning

Here are some of the most important benefits of RPA with ML:

  • RPA with ML has automated a large number of processes that have reduced costs. RPA has gotten improved learning thanks to machine learning. RPA with ML can take care of the tasks which are repetitive and can save precious resources and time.
  • The RPA tools with ML can be modeled and deployed the automation processes rapidly. The defects can be tracked in real-time.
  • These have the ability to effectively and seamlessly build along with effective release management. The robots never get tired even with ML these can increase scalability.
  • Improved throughput, decreased cycle time improved accuracy.

Can use man in the middle approach to handling low accuracy scenarios with RPA

Pitfalls of RPA with ML

  • Finding historical data for training the models is really difficult.
  • Most of the time, accuracy is less.
  • Model training takes a lot of time and resources.
  • Alignment is important for the success of every project.
  • Full Intelligent process automation can be desirable but these are never economical.

Conclusion

Investment in the new technology has been driven by the goals to increase organizational agility and the capacity of execution processes. RPA is already serving various industries but now the intelligent automation will lead the industries to a new level of innovations.

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