Abstract This paper discussed the increasing use of artificial intelligence (AI) in various industries, particularly in the form of chatbots. Chatbots are AI-powered systems that interact with humans in order to support, collect, and deliver information. The technology is used to streamline internal workflow, improve customer experience (CX) and reduce business costs. The essay noted that chatbots promised to provide streamlined service and hence ameliorate interactions between customers and companies. Because of this, chatbots as a technology is projected to have a valuation of 102$ billion by the year 2026 and is in general seen as vital in the development of accessible technology. In spite of this, consumers’ acceptance of chatbots is in relative terms low, and users’ wishes are shown to be ignored or rejected by firms implementing the technology. In part because of this low rate of acceptance, a majority of chatbot projects are expected to fail. However, the present literature demonstrated a fragmented explanation as to why this is the case. The authors hence used a qualitative research strategy to describe the important factors to account for in the implementation of chatbots. The main data collection was done through semi-structured interviews with respondents involved in these implementations. Furthermore, to be able to use the knowledge already present, a semi-systematic literature review was conducted. Through the primary collection of data, the authors presented several factors that affect chatbot implementation; including the workload before launching a chatbot, the role of chatbot suppliers, meeting user expectations, and the need for building sufficient competence in the chatbot. The literature review then enabled the authors to conduct a detailed analysis of the presented results. The analysis presents the study’s compiled data from both the conducted interviews and the literature review to demonstrate the four main influencers in chatbot implementation; chatbot supplier input, company input, customer input, and total output. The authors hope that the finding will provide a starting point for further research and assist managers in better navigating the complex stages of chatbot implementation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kau-96177 |
| Date | January 2023 |
| Creators | Daniel, Lindqvist, Viktor, Johansson |
| Publisher | Karlstads universitet, Handelshögskolan (from 2013) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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