Abstract: Tuberculosis is a key infectious disease that poses a serious threat to public health. Currently, China's tuberculosis prevention and control efforts are undergoing a strategic transformation from "passive treatment" to "active detection". However, in the process of implementing grassroots prevention and control measures, various issues continue to hinder the quality and efficiency of prevention and control efforts. In particular, the shortage of imaging diagnosis talents in grassroots medical institutions, insufficient screening efficiency, and high risks of missed and incorrect diagnoses severely restrict the efficient implementation of active detection work. The rapid development of artificial intelligence (AI) imaging diagnosis technology provides new technical support to address these challenges. This article combines the current development status of AI imaging diagnosis technology at home and abroad, systematically analyzes and sorts out its core value and current situation, application scenarios, and successful cases in active detection of tuberculosis. It deeply explores the current technical bottlenecks, application obstacles and policy challenges and proposes targeted solutions and development suggestions so as to provide bases for the standardized and large-scale application of AI imaging diagnosis technology in empowering the active detection of tuberculosis in China.