Abstract
Employing automation on cloud, on-premise, or hybridly, companies are shifting their workloads to software robots, thus reshaping the old operating models, reducing toil and creating jobs that are better suited for humans. In this context, the messaging platforms are becoming the dominant communication channel worldwide and, coupled with a raising customer demand for self-services, companies are now able to create internal and external communications with zero necessity for a new user interface. With a market size expected to continually increase in the next years, modern chatbots are impressive facilitators of human-to-robot interaction. The technologies underlying chatbots can provide natural language processing (NLP) and intent recognition, enabling them to surpass language ambiguity and jargon. Furthermore, chatbots can be integrated with common messaging applications (e.g. Messenger, WhatsApp, Slack, Viber), connect to RPA robots and other technologies. Chatbots can create visitor profiles and tailored responses, initiate conversations, have a “personality”, constantly improve, or seamlessly deflect to a human operator. Time is precious, and chatbots can manage an extensive number of operations in much less than a second, bringing cost efficiency, with better internal and/or external customer experience. Nevertheless, either employing a declarative or a conversational chatbot, businesses must select the proper solution for their current and future needs, in order to achieve an adequate return on investment. In this paper we will explore the context of the chatbot market and technologies, with a case study on the effects of chatbot deployment, thus helping organizations take better digital transformation decisions.
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Anagnoste, S., Biclesanu, I., D’Ascenzo, F., Savastano, M. (2021). The Role of Chatbots in End-To-End Intelligent Automation and Future Employment Dynamics. In: Dima, A.M., D'Ascenzo, F. (eds) Business Revolution in a Digital Era. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-59972-0_20
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