Generative AI in Clinical Dental Education: Balancing Innovation With Academic Integrity Through Teacher‐Centric Implementation

Generative artificial intelligence (AI) is transforming dental education, presenting simultaneous opportunities and challenges to academic integrity, assessment validity and clinical competency development. Faculty perspectives, the most critical yet understudied determinant of successful implementation, remain insufficiently addressed in the current literature. A narrative review of published evidence examining generative AI in dental education was conducted, with particular emphasis on faculty perspectives, assessment redesign, clinical applications, as well as ethical and regulatory frameworks applicable to the Australian context. Evidence reveals widespread gaps in faculty AI knowledge and pedagogical readiness, underscoring the need for comprehensive faculty development. Traditional assessment approaches demonstrate significant vulnerabilities to AI assistance, necessitating a fundamental redesign toward authentic evaluation of competencies that AI cannot or finds very difficult to replicate. If an AI system lacking clinical training, manual dexterity or patient interaction experience can pass examinations meant to ensure practice-readiness, the question is not how such use might be detected but what competencies those assessments are measuring, and this question should drive the choices made about assessment and its associated learning activities. Clinical integration offers genuine diagnostic and simulation benefits but risks over-reliance and deskilling without structured implementation. Australian regulatory guidance provides actionable frameworks for responsible adoption. Successful AI integration requires systematic, phased approaches that prioritise faculty readiness, inclusion of its use as an adjunctive tool, redesign of assessments to evaluate authentic clinical performance, safeguard manual competency development, and uphold ethical principles consistent with Australian professional standards, whilst remaining adaptable as AI capability continues to evolve.

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Publication Details

Journal
Australian Dental Journal
Published
2026-09-09
DOI
https://doi.org/10.1111/adj.70069
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Generative AI in Clinical Dental Education: Balancing Innovation With Academic Integrity Through Teacher‐Centric Implementation

Khaled E. Ahmed, Michael F. Burrow
Australian Dental Journal
Artificial Intelligence in Healthcare and Education
article

Generative AI in Clinical Dental Education: Balancing Innovation With Academic Integrity Through Teacher‐Centric Implementation

Khaled E. Ahmed, Michael F. Burrow
article en

Abstract

Generative artificial intelligence (AI) is transforming dental education, presenting simultaneous opportunities and challenges to academic integrity, assessment validity and clinical competency development. Faculty perspectives, the most critical yet understudied determinant of successful implementation, remain insufficiently addressed in the current literature. A narrative review of published evidence examining generative AI in dental education was conducted, with particular emphasis on faculty perspectives, assessment redesign, clinical applications, as well as ethical and regulatory frameworks applicable to the Australian context. Evidence reveals widespread gaps in faculty AI knowledge and pedagogical readiness, underscoring the need for comprehensive faculty development. Traditional assessment approaches demonstrate significant vulnerabilities to AI assistance, necessitating a fundamental redesign toward authentic evaluation of competencies that AI cannot or finds very difficult to replicate. If an AI system lacking clinical training, manual dexterity or patient interaction experience can pass examinations meant to ensure practice-readiness, the question is not how such use might be detected but what competencies those assessments are measuring, and this question should drive the choices made about assessment and its associated learning activities. Clinical integration offers genuine diagnostic and simulation benefits but risks over-reliance and deskilling without structured implementation. Australian regulatory guidance provides actionable frameworks for responsible adoption. Successful AI integration requires systematic, phased approaches that prioritise faculty readiness, inclusion of its use as an adjunctive tool, redesign of assessments to evaluate authentic clinical performance, safeguard manual competency development, and uphold ethical principles consistent with Australian professional standards, whilst remaining adaptable as AI capability continues to evolve.

Australian Dental Journal
The University of Melbourne (AU), University of Hong Kong (HK)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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