This study explores the key determinants shaping foreign language majors’ adoption intention toward Chinese generative artificial intelligence (GenAI) tools. Using an extended Technology Acceptance Model (TAM), it examines the underexplored roles of two critical social factors: perceived teacher attitude (PTA) and peer influence (PI). A quantitative methodology was adopted, utilizing an online questionnaire to collect data from 423 foreign language majors across multiple universities in China. The proposed theoretical model and hypothesized relationships were rigorously analyzed through structural equation modeling (SEM). The results identified PI and attitude as direct positive predictors of adoption intention. Notably, restrictive PI was not significantly associated with adoption intention, whereas supportive PTA showed a significant positive association. This research extends the TAM and implied that simple prohibitions or passive advocacy are insufficient to promote the effective application of AI. Educational stakeholders should take practical measures to go with the future trends in Human-Machine Collaboration.