Robotic Process Automation (RPA) vs Artificial Intelligence (AI)

Robotic Process Automation (RPA) vs Artificial Intelligence (AI)

What is RPA and what is AI? In this tug of war between the two, RPA vs AI, who wins? Read on the blog to learn their specialties and more, while an informative video awaits you.


Undoubtedly, science has gifted us with many boons and has proved the ‘impossible’ as ‘possible’. Driving never-seen-before productivity, efficacy and proficiency have only become a reality due to the benefits of Artificial Intelligence and Robotic Process Automation in the workflows. A report by Grand View Research states that the global RPA market is expected to cross $25.5 billion by the years 2027, and the AI to reach a monumental $390.9 billion by 2025. Together, RPA vs AI can play a significant role in augmenting operational efficiency and transforming how your company works. Look at this report by PWC that showcases the global RPA and AI market statistics: 

PWC report - global RPA and AI market statistics
Source: PWC

What is Robotic Process Automation? 

Robotic Process Automation (RPA) is a core technology that has been engineered to detect human workflow patterns, automate manual efforts, and interact with digital systems to take some burden off the human’s shoulder. Its usage is best known to handle rule-based processes where the manual labor intake is high, thereby, taking both, non-value added and time-intensive work off your plate. 

Further, it can connect to system APIs automatically, fill out forms, log into the given applications, automate data for CRM and ERP applications, and move files into their required destinations too. 

What is Artificial Intelligence? 

Artificial Intelligence is a data-driven and outcome-focused technology that simulates human intelligence. It derives cognitive decisions based on the inputs given to it. When you have a large volume of scattered information, AI algorithms help in sorting them out according to designated patterns. With its intelligent capabilities, AI can enhance any form of automation and can carry out decision-driven, and complicated tasks as well. 

Some of the popular AI applications include speech recognition, image recognition, chatbots, natural language generation, and customer sentiment analysis. Let us now take a dig at RPA vs AI and learn how they differ from one another. 

RPI vs AI 

While the RPA is mostly process-centric, AI is data-driven. Let me help you with an example. When RPA helps in retrieving and downloading the invoice sent to the customers, the AI algorithms are designed to help out in the relevant data extraction such as invoice number, product description, etc., and manage the variability. 

Working ProcessImitates Human ActionsSimulates Human Intelligence
Data Processing and Input Programmed by a HumanRun by Analytics 
Drive Process-drivenData-driven
EnhancementsEnhances human with process automationEnhances automation
ApproachNeeds rule-based approach, trainingNeeds intelligent algorithms, computational intelligence and statistical inputs.
Results Deterministic. Automation of repetitive tasks.Utilizes predictive analytics, ML, voice recognition

When should you deploy AI and RPA? 

It would be wrong to say that either of these intelligent technologies will be needed by the companies alone. Both their credibility and functionalities are requisite for smooth functioning. However, having said that, let us now see when do we specifically look for RPA and when for AI. 

Most of the tedious workflows might look too easy for RPA, nonetheless, in more dynamic work environments, RPA will need cognitive capabilities in order to manage highly complicated issues. And, once it is equipped with AI, RPA will render massive opportunities for the companies in the following ways: 

  • It will help in tackling high-volume data and lead to super-automatic and data-driven work processes that would no longer consume a ton of time, like was the case previously. 
  • This, in turn, will substitute human interventions to aid in managing bots and streamlining unstructured data. 
  • In the end, the employees can zero in on more on the business decisions rather than carrying out the same mundane, manual tasks that took away most of their time in their calendar. Now, they can focus on something rather productive instead. 

Regardless, after you have chosen and automated the first layer of simple processes, it is now time to see those workflows that have been tagged as ‘super complicated’ for the RPA alone to carry out. And these are your candidates for AI: 

  • The workflows in which the outcomes cannot be forecasted right from the beginning, such as the number of support tickets that will be raised by the customers, product defaults, etc. 
  • AI can be used where the processes are highly variable and do not rely on a clear-cut set of rules, such as purchase decisions, language translation, etc. 
  • It can also be deployed on the processes that rely on unstructured data from documents, images, videos, emails, and articles, such as speech to text conversion, invoice extraction, etc. 

To understand this better, let us watch this video. This Video by Mind Data AI states that Robotic Process Automation allows you to automate some simple, routine tasks that are mostly structured, rigid, and tedious to do. RPA focuses on “Doing” and “replacing”. Artificial intelligence allows you to put your minds into work by allowing the intelligence to make judgment calls that go beyond basic rule-based decision-making and focuses on “Thinking”. 

Parting Thoughts 

It is a fact that these intelligent technologies are revolutionary. Ultimately, this paves the way to support a new future of businesses where organizations can gain optimized, consistent, and automation-enabled businesses that make both the customer and company happy. Especially, in competitive times like these – when the needs of your hungry customer are never-ending, technology is something that can fuel the customer needs on the go. And, on those regards, both RPA and AI have played their respective roles and functions. In the end, it is the happiness and the satisfaction of the customers that matters, and if these technologies can partake in making that happen – it calls for a win-win!

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