Research data set, data processing (code system and variables)

This study aims to identify the factors that can lead to potential communication crises in AI-enabled chatbots, based on real user experiences. The qualitative research method used was interpretive phenomenological research, as user experiences were at stake. In this context, in-depth interviews were conducted with 12 users who experienced chatbots in solving problems with different organisations in Turkey. The data set obtained as a result of the interviews was analysed using content analysis technique. The results highlighted 4 factors while expressing both the quality of artificial intelligence and users' experiences. These are: chatbots cannot understand users, they do not create an interaction environment, they cannot produce solutions, and they are insufficient in terms of speed and time.