<p>The growing use of generative artificial intelligence (GAI) in academic research has created a need to understand graduate students’ intention to adopt this technology. This study extended the technology acceptance model (TAM) to explore the factors that influence graduate students’ willingness to use GAI for academic research purposes. We integrated partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to conduct a comprehensive analysis of technology acceptance. A survey of graduate students at a university in Jiangsu Province, China, yielded 460 valid responses. The results of the PLS-SEM study showed that perceived usefulness, perceived ease of use, and subjective norms were direct factors affecting graduate students’ willingness to use GAI for academic research. Among them, the impact of perceived usefulness was the most significant. IT self-efficacy, service quality, and facilitating conditions had indirect effects on behavioral intention. Furthermore, the fsQCA analysis revealed that there were five solutions showing high intention to use GAI. Among them, high perceived usefulness and high subjective norms were the core conditions that existed in multiple paths. This study provides valuable insights for developing educational applications and promoting the adoption of GAI in academic research.</p>