IPA is a merger between the redesign of business processes and automation tools to increase efficiency. To put it another way, it “takes the robot out of the human.” IPA is a modern generation of technologies that incorporates fundamental process redesign, robotic process automation, and machine learning at its heart. It’s a set of business-process enhancements and next-generation solutions that help information workers by eliminating redundant, repeatable, and routine activities. By simplifying experiences and speeding up operations, it can drastically boost customer experience or journey.

IPA imitates human behaviors and learns to do them much more over time. Because of deep learning and computational science developments, traditional rule-based automation levers are being supplemented with decision-making capability. The promise of IPA is increased productivity, higher worker morale, lower operating risks, faster response times, and better consumer journey interactions.

IPA is a technology that combines Robotic Process Automation (RPA) with other evolving Digital Transformation technologies. IPA is made up of five main innovations in its entirety:

• Robotic Process Automation (RPA)
• Smart Workflow
• Machine Learning (ML) & Advanced Analytics
• Natural Language Generation (NLG)
• Cognitive Agents

Robotic Process Automation (RPA)

RPA uses existing user interfaces to simplify repetitive activities including data analysis and cleansing. As with every other employee, the RPA “robot” has a user ID. It can access emails and systems, conduct calculations, create documents and reports, search files, and process customer complaints, among other rules-based tasks. The robot can completely automate and perform end-to-end operations. Only exceptions would be handled by the employee.

Smart Workflow

Algorithms that detect patterns in structured data, such as regular output data, are known as pattern recognition algorithms. This is accomplished using “supervised” and “unsupervised” learning algorithms, respectively. Until making their own predictions (based on new inputs), supervised algorithms learn from organized data sets of inputs and outputs. Unsupervised algorithms look at organized data and have instant insights into trends that are recognized. Advanced analytics has also been widely used in HR companies to identify and analyze core personality characteristics in executives and administrators to help anticipate attitudes, build career pathways, and schedule leadership successions.

Machine Learning (ML) & Advanced Analytics

Smart Workflow is a process automation program that combines functions done by humans and computers in groups. It will do this by sitting on top of RPA and assisting in the management of the whole operation. Employees may use this feature to start and monitor an end-to-end process in real-time. The Smart Workflow software will handle handoffs between various groups, including robots and humans, as well as statistical reporting on process bottlenecks.

Natural Language Generation (NLG)

These are technological engines that adopt guidelines to convert insights into natural language, resulting in smooth communications between human workers and technology. Structured output data can be imported into an NLG engine, which will automatically generate internal and external management reports.

Cognitive Agents

Some technologies merge machine learning and natural language processing to create a fully virtual agent that can perform tasks, communicate, learn from data sets, and even make decisions based on “emotion recognition.” Employees and consumers may get help from Cognitive Agents on the phone or through live chat. IPA has heavily used in the Insurance, Banking, and Financial Services industry.

In the Insurance sector, IPA is used for five main purposes:

Claim Analysis: IPA can be used to classify and annotate new claims before routing them to SEM for review. The use of IPA here increases efficiency further increasing customer satisfaction.

Medical Claims: Healthcare being a document-heavy industry uses IPA to handle unstructured records for improved patient care.

Commercial Underwriting: High volume of documentation is used in commercial underwriting. By creating criteria that IPA can use, a “score” could be rapidly produced for the customers.

Figure 1: Adoption of Intelligent Automation (Accessible in PDF Version) 

According to a global 2019 survey, nearly 40% of respondents said intelligence automation (IA) has been implemented at a functional level in their business. Another 32% of respondents predicted that this will be the case in their company in a year. Intelligent automation is the umbrella term for a group of technologies that allow digital transformation and business process automation, including robotic process automation (RPA), artificial intelligence (AI), cloud, and smart machines(Liu).

Figure 2: Statista and TNW  (Accessible in PDF Version) 

We can see a growth rate of users in the social media platforms field since 2004 as per the graph above. Technology has been growing exponentially since 2000 in every field, from gaming, television, and telephones to music, business communication, and text messages. The increase in social media is a good representation of an increase in the user base for the other

fields talked about above. Technology has become more user-friendly and in-depth in comparison to how it started in the 2000s.

To conclude, IPA is a version of automation that imitates and amplifies human actions and capabilities. Being a merger of various technologies including RPA and NLG, IPA can have numerous implications and advantages for various industries including increased efficiency and customer satisfaction. With a rapid growth in technology innovation and usage observed in the last two decades, integration of IPA in industries would be a great enhancement to the development.