Ever since its advent into the IT arena, artificial intelligence (AI) has made an enviable place for itself under the sun! Well, so has robotic process automation (RPA)! Since, both have something valuable to contribute towards automated processes, when they come together, they could create a highly skilled and intelligent digital workforce.
They Approach Problems Differently
Despite being under the same umbrella titled ‘automation’, AI and RPA display different approaches to resolving problems. For instance, AI programs can be created in a way that they can think like a human being. They can visualize all aspects of the problem, understand the language and identify a pattern. In contrast, RPA can only mimic human activities. It is an obedient robot, devoid of independent thinking. AI can understand and process all kinds of data – structured, semi-structured and unstructured. While structured data refers to information stored in a database or a spreadsheet found in web form or on an application program interface (API), semi-structured data appears on documents of all forms. An example is an invoice. The date could be in the right-hand/left-hand corner. Similarly, the VAT amount for the purchase may be visible or left out. Suffice to say that whatever the variables are, AI is unfazed and can understand them well. As for unstructured data, it refers to email content. For instance, you may send a complaint about an online-ordered dress being of the wrong size. AI uses the keywords – complaint, dress and size – for assessing the problem and giving a solution. Unlike AI, RPA’s favorite is structured data. However, some types of semi-structured information make sense too. Similar to a human being, AI changes its behavior in accordance with what the collected data demands. It can even learn new behavior. It requires no programmed instructions for either task. RPA merely moves on a straight path, following all the rules that humans input into it. AI’s magic word is ‘probably’. If you do this, the outcome may be this/that. It always leaves something to chance. RPA, however, is tremendously deterministic in its thinking. Every action has a particular outcome only, nothing more/less. Finally, AI supplies to-the-point solutions. It refuses to give broad-based or vague ones. RPA cannot do the same. Wondering why AI can’t be used more if it is so great? Well, that’s because building an effective AI-enabled algorithm is certainly not simple due to huge amount of data needed and complexity in building the logic around it.
CRPA/IPA
Their diverse ways of functioning should serve to tell you that AI is akin to a friend. It does not look down upon a system’s limitations. Instead, it works with them. This way, it converts weaknesses to strengths. Naturally, the output is valuable and relevant. RPA software, on the other hand, simply strives to control/overcome a system’s limitations, and leaves it at that. Modern business ventures see advantages in bringing both together. Their respective strengths, working in combination, will aid in completing different types of tasks, extremely efficiently. Furthermore, one’s strengths will overcome the weaknesses of the other. The bonding of AI and RPA can assist in working with different systems for improved decision-making. There will be healthy collecting and sharing of information amongst all systems too. Thus, AI, with its cognitive abilities, should be able to provide the ‘human touch’ to the workflow, thereby empowering RPA. We refer to this convergence of AI and RPA as CRPA (cognitive robotic process automation) or IPA (intelligent process automation).
Creation of a Digital Workforce
The outcome of the merger of AI with RPA is a digital workforce. This workforce refers to a team comprising of software robots. They are quite different from the human look-alikes that you see in factories, movies, etc. It is possible to rate the efficiency of each software robot on a scale of 1 to 10. Therefore, we consider the digital workforce to be scalable. These automated workers work alongside humans. They take charge of repetitive tasks or repeated processes. This permits humans to spend more time on value-adding projects. Unlike cumbersome activities, these projects/tasks require creativity, collaboration, ingenuity and empathy. Some industrial sectors have already begun to use the digital workforce. One of them is banking. For instance, banks are experimenting with advanced biometrics (physical characteristics, such as shape of face, fingerprints) for helping people open legitimate accounts. Similarly, IT companies are using chatbots to provide customer services/support. The healthcare industry, insurance companies, among others are also figuring out how to utilize the digital workforce fruitfully.
Authored by Admin
