New review maps where artificial intelligence is already helping dentists—and where caution is still needed.

A narrative review in Journal of Dentistry pulls together 120 studies to show how AI is moving from pilot projects to everyday tools across dental education, patient care, and practice operations. The authors’ bottom line: used wisely, AI can speed up learning, sharpen diagnoses, and streamline clinics—but it’s a copilot, not a replacement for dentists’ judgment.  

What’s new

• Training tomorrow’s dentists. Adaptive tutoring systems, radiograph‑reading software, and large language models (LLMs) are helping students master complex material faster. In trials, AI systems read bitewing X‑rays with high accuracy, and ChatGPT‑4 outperformed other models on periodontal exam questions—though students flagged gaps when non‑specialized AI was used.  
• Improving patient care. Across specialties, AI tools are being used to gather diagnostic information and support treatment decisions—for example, flagging early signs of disease on images—helping clinicians consider options more efficiently.  
• Smoother, smarter clinics. The review describes practical gains in four everyday areas. As illustrated in the diagram on page 6 (Fig. 3), AI is being deployed for patient scheduling and recall, EHR support (including voice dictation and auto‑generated chart notes), automated billing and insurance claims, and quality‑assurance tasks like post‑visit follow‑ups, chart audits, and credentialing. Named examples include Dentrix Voice for charting, Overjet for insurance workflows, and platforms that analyze patient feedback to improve service.      

Why it matters

These capabilities can cut administrative bottlenecks, reduce documentation errors, and enhance the patient experience—freeing up clinicians for more face time and complex decision‑making.  

Mind the gaps

The authors stress unresolved issues: protecting sensitive health data, clarifying liability when AI‑assisted decisions go wrong, and preventing bias from non‑representative training data. Even in core tasks like caries detection, reported sensitivity ranges widely (e.g., ~19–92% for occlusal surfaces; ~39–94% for proximal), underscoring the need for rigorous validation and human oversight. Regulators and institutions will need clear standards for safety, transparency, consent, and accountability before broad deployment.    

Main point

AI is already changing how dentistry is learned, practiced, and managed. For now, the smartest strategy is “human‑in‑the‑loop”: let AI accelerate routine tasks and surface insights, while clinicians keep the steering wheel—especially where the stakes are high.  

Source: “Artificial intelligence in dentistry: Exploring emerging applications and future prospects,” Sang J. Lee et al.,Journal of Dentistry (2025).