Continuous use of AI technology: the roles of trust and satisfaction

Chat Generative Pretrained Transformer (ChatGPT), a chatbot with artificial intelligence (AI) technology, opens up new directions for innovation. However, the extent to which literature has not considered the trustworthiness and satisfaction of ChatGPT. Those are important elements leading to continuous use (CU). Particularly, this study investigates the use of the ChatGPT Translate function. Requirements for task-AI-technology fit, trust and satisfaction relevant to ChatGPT Translate are addressed in this study.

Task-technology fit (TTF) theory forms the theoretical lens to examine the influences of TTF, AI-tech trust and satisfaction on CU of AI technology. A questionnaire survey was used for data collection. Structural equation modeling was employed to test the research model.

The findings show task and technology characteristics have positive effects on task-AI-technology fit. Task-AI-technology fit has a positive effect on AI-tech trust, which in turn has a positive effect on the CU of AI technology. Finally, the level of CU of AI technology by users satisfied with its responses is higher than users dissatisfied with its responses.

The results have important theoretical and practical implications for academia and industry to devise strategies and policies on a free-to-use AI system.