Training the algorithmically augmented orthodontist: competencies, curriculum design, and implementation challenges

To establish a structured framework for incorporating artificial intelligence (AI) education into orthodontic residency training, outlining the competencies required for thoughtful and responsible use of AI in clinical practice.

The framework was developed through a series of iterative discussions among orthodontic educators with experience in digital orthodontics and AI research. A targeted review of the literature in dentistry, medical education, and health care ethics was performed to identify recurring themes related to AI literacy, competency-based training, and clinical integration. Insights were synthesized into guiding principles, competency domains, and curricular components suitable for orthodontic residency programs.

The proposed framework describes (1) key guiding principles for integrating AI into orthodontic education, including patient-centered care, evidence-based evaluation, interdisciplinary collaboration, experiential learning, professional responsibility, and adaptability; (2) a phased curriculum spanning foundational AI concepts, clinical applications, patient management, ethics, and research appraisal; and (3) core competencies with measurable objectives focused on AI literacy, clinical workflow integration, ethical and regulatory awareness, and familiarity with AI-enabled orthodontic tools. Common implementation challenges, such as faculty experience gaps, limited resources, regulatory uncertainty, and assessment variability, are also discussed, along with practical strategies to address them.

Integrating AI into orthodontic education is increasingly necessary to prepare future clinicians for evolving practice environments. This framework provides a practical foundation for curriculum development and encourages broader discussion to establish shared standards for AI competencies in orthodontics.