earticle

영어

Recent developments in user-centered artificial intelligence (AI) services, especially large language model (LLM) systems, have significantly reshaped human-computer interactions by enabling more natural and conversational engagements. These advancements have facilitated the automation of corporate marketing functions such as customer support, content creation, and personalized communication. Consequently, businesses are increasingly adopting AI-driven conversational agents to improve service quality, while consumers have come to expect real-time, relevant, and high-quality responses. This study proposes a dual-path model to explore how ChatGPT’s human-like characteristics and performance-related attributes affect user satisfaction with AI services. By examining both human-like and performance factors, this research aims to offer a comprehensive understanding of AI service adoption. The findings provide valuable insights for the academic community and offer practical implications for both understanding users of ChatGPT and businesses seeking to enhance their AI-based customer engagement strategies.