RPA Vs. AI

Today's business environment is quite challenging as technologies are evolving rapidly, and there is an abundance of jargon that can perplex many of us. Two terms, in particular, are causing confusion in leading sectors: RPA and AI. Some users mistakenly believe that these two concepts are identical. To gain a clear understanding of these industrial terms and to explore how they can contribute to the growth of your business, let's delve into their true meanings.

RPA and AI are two exciting and innovative IT applications at the forefront of the digital transformation revolution. Both technologies are reshaping the world of work by augmenting employees and ushering in a new era of productivity. However, while RPA and AI have many similarities and points of crossover, they are distinct tools with their own strengths and weaknesses.

What is RPA? & What is AI?

Robotic Process Automation is a software robot that is built to mimic human activities in day to day repetitive office tasks. The software consists of the predefined set of business rules so to autonomously execute a combination of activities, transactions, tasks and business processes across software systems to deliver the desired result without the human intervention. RPA is practically a software that reduces human efforts.

Let us see how is this different from AI?

AI or Artificial Intelligence refers to the machines that are designed to simulate human emotions, judgment, and behavior. The software is a combination of cognitive automation with machine learning, language processing, hypothesis generation, analysis, and algorithm mutation to produce analytics and insights so to match the human’s capability or to excel beyond it.

RPA and AI case studies

Perhaps the most straightforward way to grasp the impact and potential of any technology is by examining case studies. In this section, we provide case studies for both RPA and AI to illustrate how they can benefit your business.

1. RPA cases study

?A top 30 US bank with assets north of $150bn was expending a lot of work hours on mortgage processes, including data entry, document processing, data verification, and more. Aside from the manual effort, these workflows were also subject to human error. The bank worked with Ernst & Young to find a productivity-improving solution.

They used an RPA solution that could seamlessly integrate within their existing IT infrastructure to handle mortgage-related manual tasks. The results were staggering, including a 2-3x boost in efficiency, savings of $1m, and a total elimination of errors.

?2. RPA Artificial Intelligence case study

Expion Health is a healthcare cost management solution based in Gaithersburg, Maryland. They assist their medical insurance clients in handling claims management information in an industry known for its fluctuating and exorbitant pricing. Their workflows were predominantly manual, as insurers submitted claims in both electronic and paper formats. This manual process restricted their team to processing approximately 75 claims per day.

Reducing the processing time per claim posed a challenge. Due to the unstructured nature of the data, a conventional RPA solution wouldn't suffice. They required a solution enhanced by AI, specifically utilizing optical character recognition and natural language processing.

Through the implementation of an RPA + AI software, they transformed paper claims into PDFs, extracting the pertinent data before transmitting pricing information to their internal system. This solution led to a remarkable 600% increase in their daily claim processing capacity.

Here is a quick checklist to help you understand which processes are best for RPA and which are best for AI.

Use RPA:

• When work tasks are high-volume, predictable, and rule-based
• When data inputs involve structured data
• When process outcomes can be determined at the start of the process

Use AI:

• When processes are highly variable and require some form of cognition, such as complex decision-making
• When data inputs involve unstructured data
• When the workflow output is impossible to forecast at the start of the process

The Future of RPA & AI

The potential of Robotic Process Automation (RPA) and Artificial Intelligence (AI), in the future is highly promising as these technologies progress and reach maturity.

The future of RPA and AI is exciting, with the potential to transform industries and improve various aspects of our lives. However, it also comes with challenges related to ethics, regulation, and societal impact, which will need to be addressed as these technologies continue to evolve.