The development of Robotic Process Automation (RPA) technology has come a long way from the days of simple screen scraping. Over the years, it has changed how companies approach their business activities, especially when it comes to scaling and streamlining processes.

A question that arises then, naturally, is – Where is RPA headed and what is the future? The simple answer to that would be – Intelligent Process Automation (IPA). And quite naturally, the past is what could provide the best perspective on why IPA is the future.

‘RPA is the application of technology that allows employees in a company to configure computer software or a “robot” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems – IRPAAI.

Deloitte defines RPA as “essentially the combination of artificial intelligence and automation.” The term RPA gained prominence in early 2000s when companies relied on the most basic of automation which is achieved by software commands following a scripted process to perform tasks within ‘Single IT’ applications.

RPA software applications took these processes to the next level by scripting tasks across multiple ‘Single IT’ applications. This enabled business relying on multiple ‘Single IT’ applications to be automated. Use of RPA has rendered obsolete the traditional forms of IT integration that were based on Application Programming Interfaces (APIs).

RPA can turn huge volumes of structured and unstructured data and facilitate the management to take data-driven decisions.  With the help of RPA, organizations can also monitor the behavior of personnel and software applications in their business or IT processes. Here are some of the processes that can benefit from RPA:

• Data-entry procedures in workflow processes such as entering  data from  claims documents into a claims management system and invoice-processing functions
• Data extraction from standard databases such as extracting customer information to file tax claims, and data migration activities from one system to another
• Routine decision-making processes such as processing insurance claims, and banking transactions

With its host of advantages, RPA growth has been exponential in the last 5 years.  According to a McKinsey report on emerging and disruptive technologies, RPA will have a potential economic impact of nearly $6.7 trillion by 2025.

RPA solutions in most companies have workflow tools functioning efficiently in a linear way. However, they have a dependency on a human-hand to fix complicated issues outside the scope of their linear functioning. RPA also has its limitations when it comes to the judgement on what, when and how to use specific information in related contexts.

The need to overcome the limitations of RPA shaped a new way of functioning that involves multiple layers of intelligence – the IRPA. In the new processes, the information imported from multiple data sources can be saved within the system and routed through different paths within the system giving way to a next level of human-like decision making.

These intelligent processes take into account factors like date and time, thus powering a more automated system workflow. IPA is based on advanced computer vision, unattended robotics, and integration with third party cognitive services.

All of these technologies work in their own unique ways. Some simply follow scripts, others are trained by humans to be intelligent through learning. And the more complex ones possess self-learning abilities. Technology will also enable a convergence of BPM and RPA tools.

Emerging technology enables new age systems to learn from its human supervisors about how to optimally utilize information. The ability of machines to dynamically adapt to new information and data has advanced these systems to become more than just robots that automate processes. As McKinsey puts it, “In essence, IPA takes the robot out of the human.”

IPA will undoubtedly become an even more integral part of the future operating models. Experts suggest that IPA will further leverage AI, eventually leading to a complete automation of processes.

Enterprises across the globe are focusing on IPA solutions that can accommodate both current and future business needs in addition to the growing market competition. And the best practice for businesses would be to fully assess the scope of digital transformation prior to adapting complete automation.