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This paper, which is adapted for publication and differs slightly from the original version distributed to American Association of Orthodontists (AAO) members in January 2026, is authored by the AAO Task Force on Artificial Intelligence in Orthodontics, and provides professional guidance for the responsible development, implementation, and oversight of artificial intelligence (AI) technologies in orthodontic clinical care. Although not regulatory, it establishes a framework to support ethical adoption, patient safety, and professional accountability in the integration of AI systems. The objectives of this paper are to preserve professional authority, promote transparency in AI development, protect patient safety, and establish a principles-based framework. These objectives will be guided through the following 6 core principles: (1) AI governance and the human-in-command, (2) regulatory alignment and risk-based oversight, (3) trustworthiness and transparency across the lifecycle, (4) patient autonomy, (5) education and clinical AI competency, and (6) operational integration and data privacy. The seamless integration of AI into orthodontic and dental care positions the orthodontist not only as the final decision-maker in the use of AI for patient care but also as the responsible party. Through transparency and a clear understanding of the underlying algorithms and learning models, orthodontists can deliver enhanced care that thoughtfully integrates technological innovation with traditional biomechanical principles without compromising patient safety, quality of care, or autonomy.
BACKGROUND: Sagittal occlusal anomalies (distal and mesial occlusion) rank first among all dentoalveolar and maxillofacial anomalies. The absence of consensus among specialists regarding diagnosis and treatment planning underscores the need for further investigation. A stable extracranial landmark, such as the forehead and the soft-tissue glabella point, enables determination of an optimal sagittal jaw position within the cranial space that is unique for each patient. However, the assessment of optimal sagittal jaw position relative to the forehead relies on manual diagnostic gauges and templates that are difficult to access. As a result, studies involving unique human landmarks in the evaluation of dentoalveolar and maxillofacial anomalies have remained largely inaccessible to clinicians. A new diagnostic platform for assessing sagittal jaw position using 3D facial photography may address this limitation. As new diagnostic approaches become available, the need arises to compare manual and software-based methods for evaluating sagittal jaw position. AIM: The work aimed to compare a manual method with a new digital method for determining optimal jaw position in the sagittal plane. METHODS: The study was conducted at the MOSORTO Orthodontic Clinic and based at the UNIDENT dental clinic network from March 1 to October 31, 2025. A total of 50 patients (25 men and 25 women) aged 18–50 years (mean age 32.0 ± 3.4 years) with skeletal occlusal anomalies in the sagittal plane were examined. All participants underwent diagnostics and orthodontic treatment planning based on unique human landmarks (Six Elements of Orofacial Harmony), first using a manual method and then with a new digital diagnostic platform. Both methods (manual and software-based) were compared across six parameters. RESULTS: Correlation analysis (Spearman rank correlation coefficient) demonstrated a statistically significant positive correlation across all parameters (p 0.0001). For most measurements, the error ranged from 3% to 8%. CONCLUSION: The new diagnostic platform for assessing sagittal jaw position based on unique human landmarks using 3D facial photography is comparable with the manual method for diagnostic purposes and treatment planning of dentoalveolar anomalies in the sagittal plane.
