Customer Adoption of AI-driven Products in the Telecommunication Industry – Barriers and Enablers

Abstract

Artificial Intelligence (AI) performance is increasingly used in the telecommunications sector. Telecom companies use chatbots, virtual assistants, and predictive systems as AI tools to serve customers better, cut costs, and respond to user needs. Despite all these benefits, most customers are unwilling to resort to AI-driven services. In this thesis, we study the motives of this reticence and what characteristics can promote more customer confidence and acceptance when applied. It is a mixed-methods study consisting of a case study of the Vodafone AI chatbot called SuperTOBi and the impressions gathered with the help of a structured questionnaire issued in Austria. Among the noted primary obstacles to using AI, the study points out distrust, emotional alienation, privacy, and unintuitive or cumbersome interfaces. Meanwhile, it singles out the key enablers such as transparency, user-friendliness, individualized experiences, and the opportunity to revert to a human agent when necessary. The thesis employs established theoretical frameworks to understand such factors better, and these include the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Diffusion of Innovations (DoI) theory. The results indicate that AI adoption in telecom relies on technical performance and customer attitudes towards using these. Based on these, the thesis provides viable suggestions to assist telecom companies in developing humanized, emotional, and customer demand-compliant AI services.

Datum der Bewilligung	2025
Originalsprache	Englisch
Betreuer/-in	Andreas Lovric (Betreuer*in)