Objective To evaluate the diagnostic value of ultrasonic artificial intelligence (AI) system in breast imaging-reporting and data system (BI-RADS) class 4 breast nodules with maximum diameter ≤2 cm. Methods A total of 210 breast nodules were analyzed in 204 patients with pathological results obtained by surgery at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine. The maximum diameter of the breast nodules was ≤2 cm. With the pathological results as the gold standard, all nodules were examined by routine ultrasound (US) and AI aided diagnosis system. The values of routine US by a senior physocian, AI (threshold value 0.65) and AI (threshold value 0.70) in diagnosing benign and malignant in BI-RADS class 4 breast nodules with maximum diameter ≤2 cm were evaluated. Results The pathological results showed that 210 breast nodules included 94 benign nodules and 116 malignant nodules. The sensitivity, specificity and accuracy of routine US in diagnosing benign and malignant breast nodules were 92.24%, 75.53% and 84.76%, respectively; the sensitivity, specificity and accuracy of AI (threshold value 0.65) were 92.24%, 71.28% and 82.86%, respectively; and those of AI (threshold value 0.70) were 90.52%, 79.79% and 85.71%, respectively. The accuracy of diagnosing BI-RADS 4a nodules of AI (threshold value 0.70) was higher than those of routine US and AI (threshold value 0.65) (79.41% vs 77.94%, 75.00%). The senior physician had the highest diagnostic accuracy of 86.36% for nodules with maximum diameter ≤1 cm using routine US. The accuracies of the AI system with threshold value 0.65 and 0.70 were 81.82% and 84.09%, respectively. Conclusion Ultrasonic AI diagnosis system can assist to improve the diagnostic efficiency of BI-RADS class 4 breast nodules with maximum diameter ≤2 cm.