Depression has become a global medical crisis. Barriers for effective depression treatment include shortage of medical professionals, inaccurate assessment, and social stigma towards depression. Leveraging artificial intelligence (AI) system in depression treatment is a possible way to remove these barriers. However, AI system has its limitations such as assessment bias. Hence, in this short paper, we propose integrating AI and human intelligence to create a task assembly AI-human hybrid for depression treatment. We then develop a research model to assess users’ preference with three service agents (i.e., human physicians, AI system, and AI-human hybrid) in terms of privacy concern and trust. We also argue that social stigma plays a moderating role in users’ service agent preference. Further, we examine the underlying mechanisms that form the users’ intention to use a certain service agent. This paper can have significant theoretical and practical implications for AI implementation in mental healthcare setting.