This study investigates the effectiveness of using artificial intelligence (AI)-assisted ultrasound screening for breast cancer detection among women in China. Shen et al. conducted a prospective study within China’s “Two Cancers” screening program, comparing AI-assisted ultrasound screening in one district with routine ultrasound screening in another. The study analyzed data from over 21,790 women, 35 to 69 years old with no prior history of breast cancer, to evaluate the differences in screening sensitivity and cancer detection rates. The screening methods consisted of a clinical examination, initial breast ultrasound screening, MAM rescreen, histopathological examination, and follow-up. Results showed that the AI-assisted screening model significantly detected more breast cancers compared to routine screening (21 vs. 9 cases, P = 0.001), and had a higher sensitivity (75% vs. 42.8%). The AI group was also more effective in detecting early-stage cancers (95.2% vs. 88.9%). However, there was no significant difference in interval cancer detection between the two methods. Overall, this study demonstrates how AI-assisted ultrasounds can improve screening sensitivity and early cancer detection rates when compared to traditional methods, providing an effective alternative for populations in which mammographies are less efficient. Furthermore, the use of AI showed to enhance the identification of "true-positive" cases, increasing the accuracy and reliability of breast cancer screening.