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Combining Artificial Intelligence with Robotic Process Automation—An Intelligent Automation Approach

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Deep Learning and Big Data for Intelligent Transportation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 945))

Abstract

Process Automation has the potential to bring great benefits for businesses and organizations especially in the financial services industry where businesses are information-intensive and experience rich data flows. This was achieved mainly via Robotic Process Automation (RPA), but the increased complexity of the Machine Learning (ML) algorithms increased the possibility of integrating classic RPA with Artificial Intelligence (AI), leading to Robotics 2.0. However, the transition from RPA to Robotics 2.0 embeds a number of challenges. To ensure that the advantages of the modern technologies can be harnessed, these issues need to be tackled. By integrating RPA with cognitive technology such as machine learning, speech recognition, and natural language processing, businesses can automate higher-order tasks with AI assisting that human perceptual and judgment skills were needed in the past. The purpose of this chapter is to identify the set of challenges the companies will face, as well as provide guidance on what preparations to be made before Robotics 2.0 can be implemented in full scale. This also provides the insights about the new intelligent automation approach based on AI integration with RPA in intelligent transportation system.

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Correspondence to Deepak Prashar .

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Jha, N., Prashar, D., Nagpal, A. (2021). Combining Artificial Intelligence with Robotic Process Automation—An Intelligent Automation Approach. In: Ahmed, K.R., Hassanien, A.E. (eds) Deep Learning and Big Data for Intelligent Transportation. Studies in Computational Intelligence, vol 945. Springer, Cham. https://doi.org/10.1007/978-3-030-65661-4_12

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