AI Precision in Orthodontics: Applications, Evidence, and Future Directions A Narrative Review

Abstract

Artificial Intelligence (AI) is transforming orthodontic diagnosis, treatment planning, and monitoring by enabling faster, more consistent, and more individualized clinical decision-making. This narrative review synthesizes current peer-reviewed literature on AI applications across the orthodontic care pathway, including automated cephalometric landmark detection, extraction and treatment-planning decision support, clear aligner design and tooth-movement prediction, biomechanical finite element simulation, real-time remote patient monitoring, face-driven soft-tissue analysis, and airway screening. Across these domains, AI systems built on convolutional neural networks and related deep-learning architectures have demonstrated accuracy that frequently approaches or matches experienced clinicians, while substantially reducing analysis time and inter-examiner variability. Key limitations persist, including dataset diversity, generalizability across imaging systems, algorithmic bias, data privacy, and the continued need for clinician oversight. We conclude that AI is best positioned as a decision-support tool that enhances precision throughout orthodontic care rather than a replacement for clinical judgment.