AI and the efficiency of technical support

Abstract

This thesis presents a preliminary study in relation to the implementation of an artificial intelligence (AI) supported chatbot in an existing customer support process. Digital technologies have become increasingly important in recent years. This has been amplified by the effects of the Covid-19 pandemic, which has seen employees increasingly working from home. Covid-19 has changed both consumer and working behaviour in a way that has further accelerated the use of many digital tools (Du Toitet al. 2020). In general, this has also increased the desire for remote support and self-service in customer service in order to minimize personal contacts outside the company. In addition, the amount of available data in this area is almost unmanageable and is growing from year to year, where by the stored data can be used profitably. Particularly in the area of customer service and support, findings from a historical analysis can make a lasting contribution to improving the customer experience (Gupta 2021). This thesis deals with the question of how the process from the acceptance of a repair request to the resolution of the problem can be optimized. Currently, there are many time-consuming intermediate steps that overshadow the customer experience with the company. In this paper, a process is proposed that utilizes an AI supported chatbot that will be able to either solve common problems remotely without the need for human interaction or automate other time-consuming intermediate steps based on existing (and future generated) data in order to improve the customer experience.The results of the survey performed within this thesis show that the implementation of such a chatbot can enable the preventive mitigation of easily solvable problems. As a result, the technical staff can concentrate on complex problems, which would result in increased efficiency in the use of existing resources. However, this study also shows that existing technologies for this application have certain limitations that need to be overcome before final implementation as part of further development steps.