Generative AI and ESL consumers’ complaint voice: the role of complaint self-efficacy in perceived complaint success

Consumers who speak English as a second language (ESL) often face challenges when lodging complaints, particularly in service environments that require clear written communication. These barriers can reduce consumers’ willingness to voice complaints and shape their expectations of whether complaining will be effective. This research examines whether generative artificial intelligence (GenAI) can support consumer voice by assisting individuals during complaint composition. Drawing on the Accessible–Interactive–Dynamic (AID) framework, we examine how GenAI writing assistance can support consumers during complaint composition. Across three experiments, we examine how GenAI writing assistance influences complaint self-efficacy and the perceived likelihood of a successful complaint (PLSC). The results show that ESL consumers report lower complaint self-efficacy and lower perceived likelihood of complaint success than native English speakers. However, GenAI writing assistance increases complaint self-efficacy and, in turn, strengthens ESL consumers’ expectations that their complaint will be successfully addressed.