RPA vs. AI/ML: Why Care About the Two? Where does IoT Fit in Picture?

RPA which stands for “Robotic Process Automation” and AI/ML as most of us know as “Artificial Intelligence/Machine Learning” are two technologies, which when used side-by-side, have the potential to replace total human intervention in most operations. Yet these two technologies are very much different in their functions and use case scenario.

Let’s learn more about the two technologies in brief and get a clearer picture of the same.

Article written by: Ankan Mitra

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Artificial Intelligence and Robotic Process Automation Visual Reference. Image Credit: Silver Touch

RPA, which is mostly self-explanatory is mainly a machine or a piece of software that can perform a pre-programmed task repetitively with efficiency and accuracy much higher than even a skilled human in that respective operation. In other words, you can say it mimics human actions with very high efficiency. However, for RPA to work efficiently, the scripting of the software must be done in a clear, precise, and scripted fashion.

Now many of you may remember using such software/program in any instance in your life, mainly people dealing with accounting, supply chain, scheduling delivery dates, etc. will relate. Yes, those pieces of software are a type of RPA and used for automating operations.

Visual Reference for applications of RPA. Image Credit: ProcessMaker

Let’s take one more example. Remember receiving “Good Morning” texts from your elderly family members on your WhatsApp every day and your “Family WhatsApp Group” getting spammed with such texts! You may develop or use a software where you’ll need to define priorly the period of receiving the text and the keyword “Good Morning” and let the software run overnight. The software shall itself get activated at the period that is set and automatically detects and delete the predefined keyword text without you taking the labour on yourself.

However, the biggest drawback of RPA is that it requires to be predefined precisely by something or someone before doing an operation. It is incapable of making its own decision or doing the operation with some variation. For example in our case, it cannot detect and delete “Good Morning” images even if it means the same.

Visual Reference of AI. Image Credit: Samsung Global

That’s right where AI comes into the picture.AI is the ability of the computer or a computer-controlled robot that helps to perform a task based on prior experiences. Here, some data of operation with variations are previously fed into the system and are deployed into action. With each operation, the algorithm stores the data obtained from each operation into its memory and analyzes the outcomes of the past experiences to improve its future judgemental decisions.

In this fashion, AI correlates and gives a more accurate guesstimate that we can trust. It mimics how the human brain would work in a situation.

Now there might be a question as to why do we use AI when humans can do the same thing with much better judgement?

That’s because a human can’t take a judgemental decision n number of times with the same efficiency every time and don’t forget that he/she will get bored doing the same. AI can simply replace human interaction at this point and get the job done quicker with the same efficiency. Mainly during when thousands of judgemental decisions are required at a single time, AIs are used. AI is mainly used as a system’s brain like in the above example where RPA fails to recognise the “Good Morning” Image, AI would recognise it as the same category and will know that it’s to be deleted but that’s it. That’s all AI can do, it can only make judgements but can’t do operations like in this case deleting the images, it is one of the main limitations of AI. AI requires some additional too (mostly RPA) to act out its judgement, here it’ll require the RPA software to perform the delete action on the images.

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Visual Interpretation of AI as the BRAIN and RPA as the LIMB. Image Credit: Kofax

You can say AI is “the brain” that takes the judgements and RPA is “the limb” that performs the required action as per the judgement. AI systems are mainly intelligence-centric/ judgemental whereas RPA systems are mainly action-centric/operational. Where RPA systems are made to perform a broader set of actions like login to a site, turning lights on at a defined time, etc. but they fail in deciding the better way to do the same or if it’s even worth doing it in the first place. AI, on the other hand, is more outcome-based, comparing data from every source which (RPA, of course, can’t do) and taking the right judgement based upon the available information provided to it.

Visual representation of integration of the two identities with their respective capabilities. Image Credit: Kofax

So, that’s how RPA and AI work hand-in-hand in today’s world and are making our lives easier and also making things happen quickly and accurately. Still, there are many more ways of application of these two technologies. Mainly they are used in supply chain automation where large quantities of goods are needed to be identified, segregated, and then shipped to their respective destinations. This not only makes the whole process faster but also reduces the total cost (by eliminating human labour) of operating the business. However, there is one more thing that is required alongside with RPA & AI, that is IoT or the Internet of Things.

Application of RPA and AI in the household. Image Credit: SenseWare

IoT devices are nothing but mainly internet-connected smart devices/sensors which functions as a sensing device for the AI to receive the information for processing, as we have already learnt that AI itself cannot act and needs additional tools to act upon its judgements, IoT behaves as “the eyes and ears” for the AI. I’ve here not even touched the tip of the “iceberg” and just tried to provide a very crude understanding of the three vast identities so that you have a holistic view of the same. These three identities cannot be summarised in just a single article and they are areas of research on their own.

A histogram representing predicted growth of RPA and AI in the coming years. Image Credit: PolarisMarketResearch

With each passing year, newer and newer applications and advancements are being done to the same to make it household stuff. However, if you have an interest in these topics, which I assume you do, as you’re reading this article and learn about the same, then you may even bring them into service in your day-to-day life just like we are!

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