Open Access

Robotic Automation Process – The operating system for the digital enterprise


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Robotic Process Automation (RPA) is going into a “maturity market”. The main vendor providers surpassed USD 1 billion in evaluation and the research they are launching these days on the market will change again radically the business landscape. It can be seen already what is coming next to RPA: intelligent optical character recognition (IOCR), chat-bots, machine learning, big data analytics, cognitive platforms, anomaly detection, pattern analysis, voice recognition, data classification and many more. As a result the top vendors developed partnerships with the main leading artificial intelligence providers, such as: IBM Watson, Microsoft Artificial Intelligence, Microsoft Cognitive services, blockchain, Google etc. On the business part, the consulting companies who are implementing the RPA solution are moving from developing Proof-of-Concepts (POCs) and Pilots to helping clients with RAP global roll-outs and developing Centre of Excellences (CoE). As a result, the experiences gathered so far by the author on this kind of projects will be tackled also in this paper. In this article will we will present also some data related to automation for different business areas (eg. Accounts Payable, Accounts Receivable etc) and how an assessment can be done correctly in order to decide if a process can be automatized and, if yes, up to which extent (ie. percent). Moreover, through the case studies we will provide (1) how now the RPA is integrated with Artificial Intelligence and Cloud, (2) how can be scaled in order to face hypes, (3) how can interpret data and (4) what savings these technologies can bring to the organizations. All the aforementioned services made Robotics Process Automation a very powerful tool since a year ago when the author did the last research. A process that was mainly not recommended for automation or was partially automated can be now fully automated with more advantages, such as: money, non-FTE savings and fulfillment time.

eISSN:
2558-9652
Language:
English