Mammography Triage in the AI Era: The Original “Real-Time” Triage Is Already in the Room

AbstractBackground The increasing adoption of artificial intelligence (AI) for mammography triage reflects the growing pressure on breast imaging services due to rising screening volumes and workforce shortages. AI-based prioritization has shown promise in improving workflow efficiency and diagnostic timelines. However, current discussions predominantly focus on algorithmic solutions and largely overlook an existing, real-time, and cost-effective triage mechanism already embedded in clinical practice: the mammography technologist at the point of image acquisition. Methods This article presents a narrative, literature-informed opinion based on published evidence and professional experience in breast imaging workflows. The role of technologists in real-time image assessment, recognition of conspicuous suspicious findings, and communication with radiologists is examined and contextualized within the broader framework of emerging AI-based triage models. Results Mammography technologists routinely perform immediate image quality assessment and may recognize conspicuous red-flag patterns during acquisition, enabling informal yet effective real-time triage and escalation to the radiologist. This human triage function may influence reading order, prompt additional imaging, and facilitate earlier radiologist attention in selected cases. The analysis suggests that technologist-based triage is scalable, economically advantageous, and already operational in many clinical settings, although it remains under-recognized and under-structured. Conclusion Mammography triage did not begin with AI. Technologist-based triage represents an existing, real-time, and low-cost resource that can be strengthened through structured training and standardized communication pathways. Rather than replacing human triage, AI should be integrated into a hybrid model that combines technologist insight, algorithmic prioritization, and radiologist expertise to optimize breast imaging workflows and patient care.