What do you feel after hearing robots with brains? With 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 which 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.
learn more about RPA, refer What is Robotic Process Automation (RPA)?
What are RPA tools?
RPA tools are several applications which 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:
Do you need to expand your knowledge on RPA tools, refer our article All you need to know 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 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 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 which 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 the 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 this 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 which 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:
- Spam email or SMS classification
- Sanction screening
- Dispute email classification
- Margin call classification
- Information extraction using unstructured documents
- Application processing
- Data migration and entry
- Periodic report preparation
- Periodic Report dissemination
Future Practical Scenarios to use ML for RPA
Combination of RPA and machine learning can help in the reduction of limitations of RPAs because by these systems will become able to learn knowledge from their previous experiences. As machine learning is developed technology which 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 the diseases like diabetes based on the person’s information.
- RPA bots are well in identifying Margin call in banking systems. Also it can be used for sanction screening process automation.
- Identify the possibility to obtain loan for their clients
- 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.
- Setting up the transportation schedules to align with actual passenger needs
Predict the future of RPA after reading Future of RPA.
Benefits of intelligent automation with software robots?
Here are some of the most important benefits of robotic process automation with ML are:
- Can use man in the middle approach to handle low accuracy scenarios with RPA
- RPA with ML has automated a large number of processes which has 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 effective and seamless 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.
Pitfalls of RPA with ML
All the things have their own limitations and challenges. Below are the challenges related to intelligent automation using software robots.
- 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.
Investment in the new technology has been driven by the goals to increase organizational agility and capacity of execution processes. RPA is already serving various industries but now the combination of RPA and Machine Learning will lead the industries to a new level of innovations.