The proliferation of chatbots across diverse business sectors has heightened the need to identify determinants of user satisfaction in human-artificial intelligence (AI) interactions. This study examines the impact of six key attributes: usefulness, entertainment, ease of use, empathy, privacy, and reliability, on consumer satisfaction with chatbot systems. Data were collected via a survey of a convenience sample of 363 participants with recent chatbot interaction experiences and analyzed using regression analysis and structural equation modeling (SEM) to construct a robust satisfaction model. The research results indicate that all six attributes may predict satisfaction (p < 0.05), with empathy emerging as a significant mediator, highlighting its critical role in shaping positive user perceptions. Chatbots that may exhibit emotional intelligence, through empathetic and personalized responses, alongside functional utility (e.g., ease of use, usefulness, and trust), may be critical to enhancing satisfaction. Empathy may be elevated from a peripheral consideration to a critical determinant of both user acceptance and sustained engagement. The research findings provide further evidence on human-computer interaction (HCI) literature by demonstrating the transformative potential of empathy-driven design in artificial agents. Practical implications urge developers to integrate affective computing and advanced natural language processing (NLP) capabilities, prioritizing emotional intelligence to optimize user experience and foster trust.