| Sumario: | The article focuses on preparing radiologic technology students for the integration of artificial intelligence (AI) in clinical imaging practice. It highlights the growing use of AI tools in image acquisition, dose optimization, quality control, and triage, emphasizing the need for radiologic technologists to develop technical literacy, clinical judgment, and ethical awareness to safely interpret and communicate AI outputs. Despite AI’s increasing clinical presence, formal AI education remains limited in radiologic technology programs worldwide, creating a gap in readiness that parallels past technological shifts in the field. The authors propose an eight-domain AI curriculum framework addressing core concepts, ethics, clinical implementation, communication, and precision learning, supported by realistic scenarios to foster critical thinking and human oversight. They also discuss barriers such as faculty preparedness, curriculum overload, and limited clinical exposure, recommending gradual curriculum integration, faculty development programs, and accessible educational resources from professional organizations to equip students for AI-augmented workflows while maintaining patient-centered care.
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