AI in Orthodontic Treatment Planning

Orthodontic planning combines a diagnosis, treatment goals and a sequence of tooth movements. AI research and software tools address parts of this workflow rather than one universally automated planning step. Reviews describe applications such as segmenting teeth in 3D scans, placing cephalometric landmarks on radiographs, generating or evaluating digital setups, and reviewing patient images between visits. A tool that automates one measurement does not establish that it can choose a safe treatment plan. The evidence base is uneven. A 2025 scoping review of AI in clear-aligner therapy found research on tooth segmentation, digital setups and remote monitoring, but reported that the identified commercial software programs were not evaluated in the included studies. A 2026 systematic review of AI-supported orthodontic planning likewise identified methodological weaknesses, including retrospective and single-center designs and limited external validation. Results for a particular model, image type or decision therefore should not be treated as proof that another tool works equally well across patients or clinics. In practice, a clinician can use software output as one input: check whether image landmarks make anatomical sense, whether a segmented tooth model is accurate, and whether proposed movements fit the patient’s diagnosis and constraints. The orthodontist must review the underlying records, discuss appropriate options with the patient and make the final clinical decisions. Digital simulations are useful representations of a plan, not guarantees that teeth will move exactly as shown.