AI applications in dentistry span multiple specialties and clinical workflows. This guide provides a structured, evidence-based overview of where AI currently has validated clinical utility — and where the evidence is still emerging.

General Dentistry

Validated Uses: AI-assisted caries detection on bitewing radiographs has demonstrated sensitivity and specificity comparable to or exceeding specialist radiologists in multiple studies. AI for bone level measurement from periapical films is increasingly validated. Clinical note generation using LLMs reduces documentation burden with acceptable accuracy when verified by the clinician.

Orthodontics

Validated Uses: Automated cephalometric landmark detection with AI achieves accuracy comparable to experienced orthodontists. AI-powered aligner staging is now embedded in commercial clear aligner systems. Tooth segmentation from CBCT using deep learning is enabling more precise treatment planning.

Implantology

Validated Uses: AI-powered CBCT segmentation for bone volume assessment, automated implant size and position planning, and AI-assisted surgical guide design are commercially available and clinically validated. Evidence supports AI assistance for reducing planning errors in complex implant cases.

Endodontics

Emerging Uses: AI detection of periapical lesions on periapical radiographs shows high sensitivity. Canal morphology classification from CBCT using deep learning is an active research area. Working length estimation assistance is being explored but not yet robustly validated for clinical deployment.

Important Clinical Note: AI tools in dentistry function as clinical decision support (CDS), not autonomous diagnostic systems. The dentist remains the responsible clinical agent. AI outputs must be verified and integrated with full clinical context — history, examination, patient communication, and professional judgment.