In response to the pervasive threat of online rumors, rumor debunking technologies based on artificial intelligence (AI) have been widely applied. However, existing research has yet to clearly reveal the factors influencing individuals’ willingness to adopt AI rumor debunking technologies and their underlying mechanisms. Based on the Task-Technology Fit (TTF) model and the Technology Acceptance Model (TAM), and incorporating the characteristics of AI rumor debunking, this study proposes and validates a theoretical model of the intention to use AI debunking technologies. The results reveal that the interdependence between humans and AI, coupled with the complexity of the task, jointly influence the task-technology fit. This, in turn, affects the credibility of AI and the intention to use it. Perceived usefulness plays a significant mediating role. Additionally, the credibility of rumors, as a set of information that conflicts with debunking, enhances individuals’ trust in AI. Perceived insecurity can increase the impact of perceived usefulness and task-technology fit on AI credibility. Innovativeness can enhance the impact of perceived usefulness on usage intention.