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Research Highlights

  • The Problem: Artificial intelligence (AI) integration in dental education faces challenges regarding institutional readiness, faculty and student preparedness, and ethical concerns such as algorithmic bias, data privacy, and academic misconduct. 

  • The Method: This literature review employed a structured narrative synthesis of qualitative and quantitative peer-reviewed empirical studies, systematic reviews, and policy reports published between 2016 and 2026 from databases including PubMed, Scopus, and Web of Science. 

  • Quantitative Finding: The study notes that European and North American dental schools have integrated AI modules, while specific regional research in China, India, and Saudi Arabia indicates early exposure enhances digital competence. 

  • Qualitative Finding: AI-driven simulations increase student technical competence and confidence; faculty perceptions range from concerns over teaching authority to recognition of pedagogical effectiveness; the "human-in-the-loop" model is emphasized to maintain clinician oversight and ethical standards.

Abstract

Background: Artificial intelligence (AI) is revolutionizing many fields by enabling machines to accomplish tasks that previously required human intelligence, such as learning, decision-making, and problem-solving. In dentistry, AI is increasingly applied to diagnostics, treatment planning, and clinical training. Its integration enhances educational experiences for students while supporting more accurate and efficient patient care.

Objective: This review synthesizes recent research on AI in dental education, highlighting global adoption trends and key pedagogical, ethical, and practical considerations.

Conclusion: AI has significant potential to enhance dental education through innovative teaching, clinical training, and data-driven decision-making. Effective integration depends on institutional readiness, ethical oversight, and stakeholder engagement. Evidence-based strategies, guided by theoretical frameworks, are crucial for supporting curriculum development, faculty training, and the responsible adoption of AI globally.

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