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Robotic Process Automation is here to stay, and is poised to revolutionize the world of work. According to Gartner, the growth of RPA could exceed 40% from one year to the next by 20201. Transparency Market Research (TMR) states that at a global level, the RPA market will reach up to $16 billion by 2024.2 This growth will be fuelled by the fact that many organizations see RPA as the first step towards introducing Artificial Intelligence (AI) into the workplace, ushering in a brave new world of increased human-machine collaboration and interaction.


Artificial Intelligence empowers RPA across business cases that include accounting, billing management, customer on-boarding, data validation, customer service inquiry routing, inventory list updating, loan qualification, risk assessment, and official document validation. RPA promises to be able to run 24/7 with no stops, no breaks, no sleeping time, no vacations, and no sick leave, without forgetting, omitting, misunderstanding, or underestimating errors and without encountering any problems.


However to make this possible RPA platforms need to be empowered with AI technologies so that they can automate the emotional and judgment-based processes. To achieve this, they need to integrate cognitive capabilities including natural language processing, machine learning, and speech recognition. Then, these automated processes can integrate a human response into their workflow. They can learn from human actions and be sure that they will be able to take the required action autonomously. The purpose is to learn, ingest, and modelize data so that the RPA platform will able to keep the intervention of a human to a minimum.


To better understand this, think of plain vanilla RPA as a mimic of human activity through UI in a non intrusive way. It can handle structured and semi-structured data, with a spectrum of possible actions that is determined by predefined rules so that the behavior of the robot is deterministic. But when AI is introduced the mirroring of human activity happens through machine vision, speech recognition, and pattern detection capabilities that can handle structured, semi-structured, and unstructured data. Machine learning lets robots learn how to process and also improve processes that leads to probabilistic behavior.


It is important to point out here that even when empowered by AI, RPA is not a human-cloning worker factory. It’s just an advanced set of software that follows rules to perform business actions. Humans are requested to build the rules, handle exceptions, bring emotional intelligence, and deal with complex and unpredictable issues.


At HCL we understand that the future of work will consist of a mix of human and robot/AI work. The focus on automating repetitive and mundane tasks will improve productivity, streamline how work is completed, eliminate errors and cut costs. This is why HCL provides RPA as a Service where you don’t have to buy the tool but buy the outcome by choosing one of our many Automation Services which bring the power of AI to your RPA processes for better business success.


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