How is RPA different from AI?
Artificial intelligence involves numerous technical terms and methods. Artificial intelligence is generally mentioned in terms of machine learning, deep learning, and robotic process automation. Although they may sound similar, they are not the same. These technologies are related to each other and are co-dependent, yet they are very different from each other. Here, you will get an overview of how Artificial Intelligence is different compared to Robotic Process Automation.
Robotic process automation
Robotic Process Automation (RPA) is concerned with automating complex and iterative business processes with the help of technologies such as machine learning and artificial intelligence. It enables machines to imitate human actions to perform a set of steps using various tools like Automation Anywhere, UiPath, Blue Prism and more. This technology is used to automate tasks and not end-to-end processes.
Artificial Intelligence (AI) is one of the most popular technologies that uses deep learning, machine learning, and natural language processing (NLP) to simulate human intelligence in machines and give them the ability to respond like a human in situations. Individuals.
Difference between RPA and AI
People generally confuse RPA for AI and vice versa. To make matters worse, many companies and suppliers use terms like Intelligent Process Automation (IPA) or Intelligent Automation (IA), making it even more confusing and daunting.
According to the IEEE Standards Association (IEEE SA) led by a panel of experts from various industries, RPA is a software robot that can act similarly to humans in performing various operations. At the same time, AI helps machines to think, get ideas and respond as human beings. In certain situations.
Thinker vs Doer
Let’s start with an example of invoice processing. Providers send invoices by mail that can be downloaded in a folder. You can extract important information from those invoices and generate invoices in your software with the help of RPA and AI.
In this case, RPA can be used to automate the email recovery process and download the files to the respective folders, and create the necessary invoices. Artificial intelligence, on the other hand, is used to read invoices and extract relevant data intelligently.
All tasks in RPA must be scheduled, so it is not possible to educate the robot on the exact place from which they need to extract the data. Therefore, artificial intelligence helps to decipher data like a human being intelligent.
In simple terms, RPA is a doer, while AI is a thinker. RPA strictly follows the rules and seamlessly executes iterative processes, while AI handles a massive volume of data and gets information from it by finding patterns.
Data-Oriented vs Process Oriented
Another key difference between RPA and AI is that AI is completely data-based, while RPA is process-based.
RPA focuses on automating redundant, rule-based operations that generally require interaction with numerous different IT systems. However, AI focuses on the quality of the data. Then choose and train proper ML algorithms to recognize the patterns and take the necessary actions.
In the example above, several good quality invoice samples are used to train the ML algorithms so that you can recognize the patterns and extract valuable information from them accordingly.
Combination of RPA and AI
Both RPA and AI are two of the most popular and widely used tools. However, their combined use in Business Process Automation is a force to be reckoned with. AI in integration with RPA speeds up the automation process and develops an automation continuum.
The independent processes would extract comprehensive responses and then transmit it to the RPA system to complete the process. This process is faster, with continuous automation.
The future of these technologies is growing rapidly as more organizations demand solutions that aid in business productivity and efficiency while reducing cost. These technologies will soon lead to complete automation in almost all business sectors, including finance, banking, insurance, and healthcare. Industries like telecommunications and digital marketing have already been fully automated.
Artificial intelligence integrated with RPA helps analyze, categorize, and extract unstructured data to make it functional and improve the outcome of complex RPA workflows. Meanwhile, RPA is an ideal technology for adapting cognitive skills. Organizations benefit greatly by using these two technologies on a single platform to automate business processes.
Best practices in integrating RPA and AI
RPA and AI are used in numerous applications today. Some of the best practices you can follow to make the most of integrated technologies.
Focus on results
Like most future and trending technologies, following a step-by-step process in these combined technologies without any future goals will not provide good results. You must start by setting your goals.
You can achieve the desired results through effective governance that enables the system to identify where technologies can be implemented. Furthermore, you can regularly monitor the result and determine the real solution.
Treat embedded technologies like the digital workforce.
Another effective way to implement these technologies is to view them as digital workers who have different skill sets than humans. Once considered digital workers, the organization’s functional units treat technologies like a person in the workplace that enables them to complete more tasks in less time and with greater efficiency.