The Impact of UTAUT2-Based Artificial Intelligence Technology on User Satisfaction through Actual System Use

Artificial Intelligence (AI) is a computer system that performs perception, reasoning, learning, and language abilities similar to humans, making it a core technology of the Fourth Industrial Revolution. Particularly, generative AI, which creates new content such as text, images, and music through large-scale data learning, has garnered significant attention. This technology utilizes artificial neural networks and machine learning to understand user intentions, learn from data, and generate various types of content. AI is defined as a technology that implements human intelligence-related functions such as learning, cognition, and reasoning using the concepts and tools of computer science. This study aims to analyze the impact of AI-based UTAUT2 characteristics on user satisfaction. The research targets general consumers who use AI services, and statistical analysis was conducted using Smart PLS 4.0. The purpose of this study is to analyze the impact of UTAUT2 characteristics in the context of artificial intelligence (AI) on user satisfaction. The research subjects were general consumers who use AI services, and statistical analysis was conducted using Smart PLS 4.0. The results of the study are as follows. First, performance expectancy had a significant positive effect on behavioral intention. Second, effort expectancy had a significant positive effect on behavioral intention. Third, social influence did not have a significant positive effect on behavioral intention. Fourth, facilitating conditions did not have a significant positive effect on behavioral intention. Fifth, trust had a significant positive effect on behavioral intention. Sixth, personal innovativeness had a significant positive effect on behavioral intention. Seventh, behavioral intention had a significant positive effect on actual system use. Eighth, actual system use had a significant positive effect on user satisfaction. Therefore, this study empirically verified the relationships between AI technology’s behavioral intention, actual system use, and user satisfaction based on the UTAUT2 model. Performance expectancy, effort expectancy, trust, and personal innovativeness were identified as significant factors influencing the acceptance intention of AI technology. Furthermore, behavioral intention was shown to lead to actual system use, which, in turn, positively influenced user satisfaction. Based on these findings, AI technology developers and companies should enhance user experience, build trust, and strengthen technical support to maximize AI technology adoption and user satisfaction.