V3I10P16

Artificial Intelligence in Dentistry: Applications in Modern Diagnosis, Treatment and Dental Business Management

Dr. Althaaf Khan^1*

Abstract

Background and objective: Artificial intelligence (AI), particularly deep learning, is moving from research into routine dental practice. This narrative review synthesises current evidence on AI in modern dental diagnosis, treatment and dental business management, and appraises the barriers to safe adoption.

Methods: Targeted searches of PubMed-indexed and publisher-hosted literature, together with South African regulatory sources, were carried out in October 2026 using combinations of terms for AI, deep learning, dentistry, diagnosis, treatment planning, practice management and ethics. Systematic reviews, randomised and diagnostic accuracy studies, ethics frameworks and legal instruments were prioritised and synthesised narratively.

Results: Diagnostic evidence is strongest for radiographic caries detection, periodontal bone loss assessment and oral lesion screening. In these tasks, convolutional neural networks matched or exceeded dentists on controlled datasets, and one randomised trial showed improved sensitivity for enamel caries. In treatment, AI supports restorative diagnosis, cephalometric analysis and implant planning, although much of the evidence is preclinical and of low certainty. Business applications such as scheduling, claims preparation and patient communication are expanding quickly but rest mainly on non-peer-reviewed sources. Limited generalisability across centres, a risk of overtreatment, sparse ethical reporting and data-protection duties remain major concerns.

Conclusion: AI is best positioned as a supervised decision-support tool. Prospective multicentre trials, transparent reporting and compliant data governance are needed before routine reliance.

Keywords:

Artificial intelligence; deep learning; dentistry; diagnostic imaging; practice management; dental ethics