Literature Aalst, W.M.P. van der, Bichler M. & Heinzl A. (2018). RoboticProcessAutomation. Bus Inf Syst Eng, 60(4), 269-272, https://10.1007/s12599-018-0542-4 Abbott, K.R. & Sarin, S.K. (1994). Experiences with Workflow Management: Issues for the Next Generation. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work. (pp. 113-120). New York: ACM. Aguirre, S. & Rodriguez, A. (2017). Automation of a Business Process Using RoboticProcessAutomation (RPA): A Case Study. In Workshop on Engineering Applications, 27 September 2017 (pp
The paper concentrates on the issues of applying smart technologies in the manufacturing processes. The author includes in it brief descriptions of the smart technologies that contributed to the emergence of Industry 4.0 concept. Additionally, based on reports and surveys conducted on a global scale regarding the application of intelligent technologies, the author analyses the current state of implementing these technologies in manufacturing processes and provides forecasts regarding the adoption of the solutions based on Artificial Intelligence in global enterprises in the near future.
References Le Clair, C., Cullen A., King M. (2017). The Forrester Wave™: RoboticProcessAutomation, Q1 2017, Retrieved from http://reprints.forrester.com/#/assets/2/661/'RES131182'/reports . Willcocks. L., Lacity, M., Craig, A. (2015). The IT Function and RoboticProcessAutomation, The Outsourcing Unit Working Research Paper Series, Paper 15/05. The London School of Economics and Political Science, London, UK. Willcocks, L., Lacity, M. (2015). RobotProcessAutomation: The Next Transformation lever of Shared Services, The Outsourcing Unit Working Research
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.
manufacturing. An example for this is a Japanese company  producing lettuce
that plans to use robots to harvest plants. The other kind of robotics is the
business process automation or roboticprocessautomation. These robots do not
have hardware, but with software that can be taught to execute those repetitive
processes which are too monotonic for human workers, ergo can be much more
effective and faster.
Artificial intelligence can be a key element in state-of-the-art solutions for
helping blind people. Many existing ways of its application can be