Objective To evaluate the diagnostic value of an artificial intelligence (AI)-assisted breast ultrasound system in the assessment of breast masses, with a focus on analyzing its role in optimizing Breast Imaging Reporting and Data System (BI-RADS) classification and reducing unnecessary biopsies. Methods A total of 243 pathologically confirmed breast masses from 222 patients were retrospectively included. Conventional ultrasonograpny (US) and BI-RADS classification were performed by junior physicians, and an AI system was used to collect images and perform automatic classification according to BI-RADS standards. BI-RADS 2-3 assessed by US and AI were regarded as benign, while BI-RADS 4-5 were defined as malignant. Pathological results were used as the gold standard to compare the diagnostic efficacy of US and AI. Results Pathological examination revealed 126 (51.85%) malignant and 117 (48.15%) benign lesions among the 243 breast masses. Receiver operating characteristic (ROC) curve analysis showed that the AI system achieved an area under curve (AUC) of 0.874 for discriminating malignant and benign breast masses, significantly higher than the 0.839 of US (P＜ 0.001). The specificity and positive predictive value of AI were 79.49% and 83.33%, respectively, which were better than the 70.94% and 78.21% of the US, whereas the sensitivity (95.24% vs 96.83%) and negative predictive value (93.94% vs 95.40%) were slightly lower. In BI-RADS 4a masses, the diagnostic accuracy of AI (73.91%) was higher than that of US (57.50%). AI downgraded 15 cases of BI-RADS 4a masses, of which 13 cases (86.67%) were benign, thus avoiding unnecessary biopsy; yet there were 2 cases (13.33%) of false negatives. Conclusion This AI-assisted breast ultrasound system can improve the diagnostic performance of junior physicians and enable accurate downgrading of BI-RADS 4a masses, thereby reducing unnecessary biopsies. However, it still has limitations in identifying atypical or occult lesions and requires comprehensive judgment based on clinical information.