Besides definition, not many can differentiate between RPA and AI. Robotic Process Automation is an application technology that allows a specially designed software or robot to learn and perform a set of pre-fed processes. It learns from algorithms made by domain experts and follows them to the T. They are an improvement over manually managed function because they can perform repetitive tasks without getting tired. Also, they are much more accurate and faster.

RPA is commonly used to capture data, process transactions, and communicate with other software and digital systems. However, it has limitations and challenges. Enterprises need Artificial Intelligence for a true breakthrough in the way organizations across the world work. To bring about groundbreaking changes, AI is the technology you need.

If you are planning complete digital transformation where AI will play an important role, RPA is a good beginning to make. It will introduce you to the benefits as well challenges that come with the adoption of such technology.  These challenges could be related to the limitations of the technology and its adoption. Besides, there could be challenges in terms of resistance from the existing workforce. AI is expected to throw more and bigger challenges. Working with RPA is a good way to get a feel of this huge change organizations have been planning.

Introduction to RPA first time at the workforces, at large, will be exposed to technology that is capable of such massive amounts of work. Besides understanding that is it an opportunity for growth and advancement, it helps them understand the kind of knowledge and skill upgradation they need to handle it. Training the workforce and making them ready to work alongside such capable machines is going to be a time-taking and extremely challenging process.

A company seeking to realize the full potential of AI can start by:

• Put the basics right: RPA provides the foundation for AI by providing automated pre-existing processes, which can be enhanced with AI. Making AI work requires domain knowledge, data and an understanding of the task and scale at hand. It may also require an overhaul or redesign processes that can affect the right implementation of AI.
• Onboarding team: Man and machine can co-exist to complement the tasks at hand by integrating human intelligence with machine learning. A new mind-set, shifting the focus to deliver on customer service and targeted KPIs, will be needed for this transition.
• Embrace to innovate: Artificial intelligence solution integrates with existing process automation and with more technology integration, can create a highly adaptable and nimble business capability.    

In some cases, adopting RPA will not yield results as expected. This will be a great lesson for those who are throwing in money without proper knowledge and planning. And Artificial Intelligence is going to be a bigger investment, so planning is important. It is going to be a complicated integration of technologies that will need experts to look over, supervise and control the web.