Artificial intelligence (AI) is increasingly used in various industries, including academic research. This study examines the drivers that influence PhD researchers’ adoption of AI academic tools, using the technology acceptance model (TAM). We propose an extended version of the basic TAM framework, incorporating perceived benefits, self-efficacy, and perceived trust in addition to perceived usefulness and perceived ease of use. Structural equation modeling (SEM) is used to test the model's validity. Our findings indicate that perceived usefulness positively affects PhD researchers’ attitudes toward using academic AI tools, while perceived ease of use, self-efficacy, perceived benefits, and perceived trust do not. We also found that PhD researchers’ attitudes toward using academic AI tools predict their behavioral intention, which ultimately determines their actual behavior. To the best of our knowledge, this is the first study of its kind in this area.