Artificially intelligent chatbots are rapidly gaining popularity in customer service, and they can offer businesses benefits such as increased stock prices and low-cost, efficient service. However, customer trust and satisfaction with these chatbots are often low. Most current research focuses on which business benefits artificially intelligent systems can yield, and less focus lies on how to create satisfactory experiences for the customers. This study examines which chatbot characteristics that build customer trust and satisfaction, and identifies the types of inquiries where customers prefer artificially intelligent chatbots over human customer service agents. An online questionnaire was conducted with 47 participants, primarily 18-24-year-old females from Sweden, with a university degree and high comfort with modern technology. The data analysis, using the Wilcoxon signed-rank test and an investigation of the mean and median scores, revealed no characteristic was significantly more important for trust than for enhancing experience. However, anthropomorphism was indicated to have some importance for trust, though not statistically significant. Machine reading comprehension, perceived accuracy, and privacy concerns were found to be important for a positive customer experience. Participants preferred artificially intelligent chatbots over human customer service agents only for basic information inquiries. The findings support existing theories such as the service quality model and can provide guidance for businesses wanting to implement artificially intelligent chatbots in customer service.

Background: In today's society, the rapid growth of online shopping among consumers has resulted in the widespread adoption of artificial intelligence powered chatbots by businesses. Despite this, previous research has not focused on where customers place their attitudes towards AI-powered chatbots in e-commerce. The ABC model of attitudes, which includes affective, behavioral, and cognitive components was used to examine how attitudes are formed towards AI-powered chatbots. Purpose: The purpose of this study is to explore consumers' attitudes towards AI-powered chatbots utilized in e-commerce. Methodology: Because the study has an exploratory and inductive approach, a qualitative research strategy was selected. It was determined to use a generic purposive sampling in which ten participants were chosen as part of Generation Z. A semi-structured interview was conducted in which questions were posed regarding the ABC model and the characteristics of AI-powered chatbots. To analyze how attitudes are formed and what they are, grounded theory was used to code the interviews to established consumer attitudes categories. Findings: The findings demonstrate that consumers' attitudes towards AI-powered chatbots used in e-commerce varied from being positive, negative, or mixed. This is due to the factors that contributed to the formation of attitudes.