[Purpose/significance] After experiencing unprecedented user growth, generative AI has encountered a sig⁃nificant decline in user scale for the first time. Identifying and analyzing the key factors influencing generative AI user discontinuance behavioris of great significance for optimizing user experience, enhancing user stickiness, and promot⁃ing the healthy development of the generative AI industry. [Method/process] This study used a combination of litera⁃ture survey and Delphi methods to systematically and comprehensively distill the influencing factors on discontinuance behavior among generative AI users, and identified and analyzed the key influencing factors using the DEMATEL meth⁃od. [Result/conclusion] The research findings indicate that: the discontinuance behavior of generative AI users is in⁃fluenced by 20 influencing factors in four dimensions: user factors, information factors, platform factors, and environ⁃mental factors; algorithmic literacy, degree of intelligence, degree of anthropomorphism, competitive environment and other 10 influencing factors are all key influencing factors of generative AI users′ discontinuance behavior; generative AI platform managers should reduce the occurrence of users′discontinuance behavior by deeply understanding users′ needs, improving users′ algorithmic literacy, establishing a social interaction platform and other aspects.