Why Organizations Must Consider Intelligent Automation Over Robotic Process Automation

Leading organizations are doubling down on tech investments, such as automation, AI, and cloud to minimize the impact of the crisis, and are identifying opportunities to survive and thrive in the next normal. According to Sneha Kapoor, Research Manager at IDC Financial Insights Asia/Pacific, the pandemic has changed the expectations and priorities and institutions are also now increasingly leveraging the power of Intelligent Automation (which also includes RPA along with other technologies and solutions) to resolve their myriad business problems and achieve goals such as enriching customer experience, optimizing operational efficiencies, and even, generating new revenue streams[1].

The reason behind RPA’s growing popularity is clear; it provides businesses with the means to automate often mundane processes once reserved for human workers. This not only frees up the human workforce to focus on more fulfilling tasks, encompassing creativity, empathy and critical thinking, but also means these tasks are being performed quicker and without error. This, in turn, leads to higher levels of employee satisfaction, major cost savings, increased productivity, quicker digital transformation and brings numerous other benefits to organizations.

As the digital landscape continues to grow and evolve, RPA is coming up short in several areas. This is where intelligent automation (IA) comes into play. IA incorporates technologies such as artificial intelligence (AI) and machine learning (ML) which, when combined with RPA, enables automated workers to learn from and collaborate with their human counterparts on more cognitively demanding processes.

Where does RPA fall short?

Put simply, RPA has limitations. It’s rules-based, meaning it can only deal with the linear-processes it has been programmed to deal with. This is great for tackling predictable and repetitive tasks and can be used effectively to complete high-volume actions in a fraction of the time they used to take, but it cannot comprehend more diverse or ambiguous processes.

It is this gap that IA can bridge. It encapsulates a number of AI technologies, including machine learning, structured and unstructured data interaction, intelligent document processing and natural language processing. If you combine this with the interactive capabilities of RPA, you then find yourself with an automation system capable of processing a much wider array of higher-function tasks.

Is there a benefit to starting with RPA before incorporating IA?

RPA is the foundation on which IA is built, working in tandem with AI to deliver intelligent automation. RPA is the platform that delivers AI capabilities to your processes. It’s a symbiotic, win-win relationship. AI gives RPA the enhanced capabilities needed to automate increasingly complex tasks, such as interacting with people, making decisions, reading, writing, and understanding documents. At the same time, RPA makes it much easier to incorporate AI into your organization because it delivers and implements AI directly into processes in a structured and easy to set up way.

For example, by incorporating intelligent automation, with human-in-loop features, Midland Credit Management (MCM), which works with consumers to resolve their past-due financial obligations, was able to automate several of its critical business processes and bring down the cost of operating their service lines. At present, the company has more than 50 digital workers across their business units, with plans for scaling further depending upon our evolving business needs.

This enhanced agility, across business operations, has led to incremental benefits, and thousands of hours have been returned to the business. The applications of combining AI and RPA, as is the case with IA, are almost limitless.

Is it too late to move to IA?

At its core, Intelligent Process Automation (IPA) is an emerging set of new technologies that combines fundamental process redesign with robotic process automation and machine learning. It is a suite of business-process improvements and next-generation tools that assists the knowledge worker by removing repetitive, replicable, and routine tasks. It can improve customer experiences by streamlining and speeding up processes.

Alongside the rest of the technology industry, the world of automation continues to develop rapidly. It can be immensely frustrating (not to mention costly) to invest in a current technology, only for the market to have moved on by the time you’ve implemented it within your organization. The good news here is that RPA and IA are intrinsically linked – so even if you’ve made a hefty investment into robotic process automation, it isn’t too late. The likelihood is that the system you’ve adopted will provide a solid framework from which to start your IA journey.

Pivoting to IA will help you maintain a competitive edge and is something many businesses are already taking advantage of. According to Deloitte’s annual automation survey, 73% of over 400 organizations surveyed around the world have begun integrating IA – a stark jump from the 58% reported the year prior. On top of this, Gartner has named ‘hyperautomation’ (which encompasses IA) a top strategic technology trend for the past three years, with IA’s scalability and ability to upend the traditional business model to stoke productivity, innovation, efficiency and ultimately ROI contributing to its rising popularity.

With the adoption and value of intelligent automation only set to continue, those businesses who future proof their operations now by integrating IA into their organization will reap the rewards of continued growth and stability for many years to come.