Understanding the role of AI in Dental Education: A rapid evidence assessment

The review aims to explore how AI is defined and applied in dental education and training, and how providers have responded through curriculum and training, the emerging challenges (including those related to EDI), and what strategies or frameworks exist to evaluate and mitigate any associated risks.

Methodology

The review identified 1,424 records and after full-text assessment, the remaining 75 records were included in the final analysis. The evidence was notably recent, with 62 records (82.7%) published in 2024 or 2025.

The literature included cross-sectional surveys, mixed-methods studies, randomised and quasi-experimental studies, comparative evaluations, pilot studies, qualitative research, curriculum-development exercises and consensus-based frameworks.

Most of the evidence was international but retained a strong UK focus. Other contributions came from the United States, Turkey, China and Canada, while additional studies were undertaken across Europe, South and Southeast Asia, the Middle East, Latin America and other international settings.

Key findings

• In classroom-based teaching and learning, evidence suggests potential educational benefits from AI in personalised study support, formative assessment, case-based learning, and rapid feedback, with early studies indicating improvements in learner confidence, motivation, and some performance outcomes.
• In clinical education and simulation, the report identifies simultaneous benefits to both learners and patients. A plausible patient-safety benefit where digital simulation environments facilitate rehearsal, feedback, and skills development without exposing patients to avoidable risks. The students benefit from immediate feedback that can enhance their knowledge, skills and confidence in performing surgical skills in preparation for real-world patient care.
• AI tools can assist applicants in drafting personal statements and aid institutions in screening applications, potentially enhancing efficiency and ensuring equity for disadvantaged applicants.
• When looking at the potential disadvantages of the use of AI in dental education, the report repeatedly highlights concerns that use of AI could affect students' ability to develop clinical thinking, professional judgement, and safe decision-making skills.
• Interview participants expressed both cautious optimism, particularly regarding administrative efficiency and structured learning support, and explicit mistrust concerning treatment planning, accountability, and patient privacy risks, including potential neglect of data protection requirements in routine use.
• A recurring theme is that certain AI systems can generate outputs that seem authoritative yet are inaccurate. This includes fabricated or unreliable references in academic tasks identified as “hallucinations”.
• Excessive reliance may diminish critical thinking and problem-solving abilities, and usage in assessment settings poses challenges to academic integrity and authenticity, affecting the validity of progression decisions and, consequently, patient safety when graduates begin practice.
• Limitations of AI were particularly pronounced in image-dependent fields, which are crucial to dentistry. AI can sometimes find it difficult in interpreting radiographs and managing procedural workflows involved in taking and analysing radiographs. Therefore, AI can be utilised as a supplementary tool rather than the sole reliance on its use for diagnostics.
• Ethical concerns were identified in relation to professional accountability and AI misuse, and the lack of emotional intelligence and empathy, which is central to patient-clinician interactions.

The report proposes several actions, including the adoption of explicit and auditable governance procedures by educational institutions which will help identify and highlight acceptable and unacceptable uses of AI tools in learning and assessment. The report suggests that both learners and educators need structured preparation to evaluate accuracy, recognise limitations, manage uncertainty, and uphold human accountability, aligning with the Safe Practitioner emphasis on behaviours and the GDC’s core standards of professionalism and competence.