Robotic Process Automation is a technology that allows a software (robot) to learn and perform a set of pre-defined tasks across multiple applications. Unlike humans, robots can work nonstop, do tedious and repetitive tasks without getting tired or having the need to take breaks in between. Robots provide output more quickly and accurately when compared to humans. If we deploy a robot to do mundane tasks, a human can be assigned to do other activities that a robot can’t, like empathizing and building relations. On the other hand, robots can support IT processes, do back-office work resulting in increased productivity without actually utilizing a full-time employee. RPA works best in industries that have a high-transaction rate of repetitive tasks.
As robots don’t have intelligence of their own, it severely limits the extent to which automation is possible, as there may be a lot of varied inputs and processes that require decision-making at different stages. To bring in some intelligence to automation, we must look at Artificial Intelligence technologies. AI has the ability to use its own logic and understanding to perform tasks. AI can learn to take decisions on its own, based on rules created by humans, and can learn by failing too, which is popularly known as machine learning.
AI includes multiple technologies that study the different facets of intelligence, including Natural Language Processing (NLP) and Machine Learning (ML). NLP and ML are more advanced than RPA. Other technologies used in AI include Virtual Agents, Biometrics, and Image Recognition. Virtual agents make use of chatbots that are programmed in a way that it can respond to human queries. A lot of applications use a virtual agent as the first point of contact for interaction with customers. Biometrics are used for identification and analysis of the human body e.g.; fingerprint can be used for entering the in-time or login time of an employee. Image Recognition is used for identifying and distinguishing an object in a video.
To explain in layman terms, RPA depicts human actions whereas AI depicts the intelligence of a human. RPA does not have the ability to learn from its mistakes whereas AI can keep learning from its own actions. RPA performs tasks that are clearly defined and where no thinking is involved. However, AI is a step further from RPA as it can learn and analyze and can give improved output to the user through training. AI differs from RPA as it can include voice and facial recognition.
Intelligent Automation (IA) combines RPA with AI technologies as per business needs to maximize the value of automation. Organizations can use IA to provide virtual assistants to their customers across chat and voice channels. The organizations that use IA can surely see an increase in their productivity, accuracy and understand the needs of their customers better by directly connecting with them. It also leads to a reduction in costs.
The ideal combo is one where RPA is combined with AI where AI helps yield better results. Which directly results in the expansion of the scope of automation within the enterprise.
As we already learned, to maximize value from automation and expand its scope, a blend of RPA with AI technologies will result in Intelligent Automation to empower rapid end-to-end business processes and considerably more.
IA offers many advantages that can be incorporated by organizations so that efficient solutions can be provided to the clients. The advantages are as follows:
- Increased productivity that enable automated applications and processes to run faster.
- Reduced costs – Automation ensures increased productivity leading to decreased manpower costs.
- Improved accuracy – Work done by an automated bot has less errors than done by humans.
Let’s look at one of the use cases where IGT incorporated RPA technology for a leading airline. This technology helped the airline cabin crew staff update their status of flying with the help of chatbots. The chatbot that interacts with the attendants shares updates about last minute changes in the staff on a particular flight.
IGT has deployed IA solutions in multiple domains like travel, hospitality and healthcare. With IA, IGT has improved its customer experience by optimizing back-office operations and increasing process efficiencies. By incorporating IA in contact center processes, it has further been able to handle surges in call center volumes, provide proactive customer service, and automated personalized messages for many of its clients.
Ayushi Jain is a Module Lead in RPA at IGT Solutions. She has 8.5 years of experience in the IT industry and has rich work experience in the Travel and HealthCare domains. Ayushi has obtained various certifications in UiPath and Automation Anywhere. She loves to travel and explore the untouched beauty of nature and enjoys reading fiction in her free time.