现有的人工智能（Artificial intelligence，AI）服务补救策略研究大多集中在事后阶段，但由于缺少人类员工的参与，事后补救的效果难以确定。因此，AI事前预防性服务补救及其效果问题亟待探索。基于期望不一致理论，本研究探究了AI预防性补救对顾客满意度的影响及其中介机制，并进一步揭示了在不同失败类型情境下，AI预防性补救作用效果的差异。通过3个实验研究发现，存在（vs.不存在）AI预防性补救可显著提升顾客满意度；感知尊重与感知风险在这一过程中起到双重中介作用，其中感知尊重发挥正向中介作用，感知风险发挥负向中介作用，且正向中介作用强度显著高于负向中介作用。另外，相比于结果失败，过程失败情境下AI预防性补救对顾客满意度的提升效果更显著。本研究丰富了AI服务补救的理论成果，也为服务商采取AI预防性补救提供了理论指导。

Existing research on AI service recovery strategies mostly focuses on the post-service stage. However, due to the lack of human employee involvement, the effectiveness of post-service recovery is hard to determine. Therefore, the issue of AI preventive service recovery and its effectiveness urgently needs to be explored. Based on the Expectation Disconfirmation Theory, this paper investigates the impact of AI preventive recovery on customer satisfaction and its mediating mechanisms, and further reveals the differences in the effectiveness of AI preventive recovery under different failure scenarios. Through three experimental studies, it is found that the presence (vs. absence) of AI preventive recovery can significantly enhance customer satisfaction. Perceived respect and perceived risk play a dual mediating role in this process, where perceived respect has a positive mediating effect, and perceived risk has a negative mediating effect, with the positive mediating effect being stronger than the negative one. In addition, compared with outcome failure, AI preventive recovery significantly improves customer satisfaction in process failure. This paper enriches the theoretical findings on AI service recovery and also provides theoretical guidance for service providers to adopt AI preventive recovery.