With the rapid development of wireless communication technology and the increasing complexity of application scenarios, traditional radio communication quality inspection methods face numerous challenges in terms of efficiency, accuracy, and adaptability. In recent years, the introduction of artificial intelligence (AI) and automation technologies has brought groundbreaking advancements to this field, significantly enhancing capabilities in signal detection, quality assessment, and system optimization. This paper integrates multiple research findings to explore the applications and impacts of AI and automation technologies in radio communication quality inspection.