Artificial Intelligence in Dental Education: International Perspectives from Vietnam
Dr Ali Nankali explores AI's growing role in dental education, emphasising responsible integration, ethical governance, staff development and enhanced clinical reasoning.
Over the past three years, developments in artificial intelligence (AI), particularly in generative tools and data-driven decision-support systems, have shifted AI from a predominantly theoretical area of research to technologies that are increasingly accessible to educators and learners, for example through their use in teaching support, formative assessment, and clinical case-based learning within healthcare education worldwide. Dentistry, in particular, is experiencing accelerated digital transformation, with AI shaping how diagnosis, treatment planning, educational delivery, and academic management are approached.
During 2025, I delivered approximately ten invited international talks focused on AI and digitalisation in dentistry and dental education. These invitations built on my longer-standing work in digital dentistry and postgraduate education, alongside a more recent focus over the past three years on the responsible use of artificial intelligence within teaching, assessment, and academic practice at Queen Mary University of London. In particular, interest was driven by the outcomes and experiences of QMUL postgraduate students shared through academic networks, as well as published work and conference discussions addressing practical and ethical questions around AI adoption in dental education. These engagements provided a valuable opportunity to observe how different institutions are responding to AI, the challenges they face, and the questions most commonly raised by academic leaders and clinicians. In November 2025, this included delivering extended teaching sessions in Vietnam to representatives from a wide range of dental universities, encompassing both public and private institutions.
The sessions were attended by senior academics, educational managers, and clinical leaders, all seeking practical insight into how AI can be meaningfully embedded within dental education and clinical practice. The sessions focused on two key areas:
- AI and digitalisation in dental teaching and academic management
- Practical applications of AI in diagnosis, treatment planning, and clinical workflows
What stood out most was not only the high level of engagement, but the nature of the questions raised. Participants were particularly interested in the practical realities of AI implementation: how these tools can be introduced safely, how staff can be supported, how ethical concerns can be addressed, and how AI can enhance — rather than disrupt — existing educational structures.
There was strong interest in understanding how institutions in the UK, and particularly at Queen Mary University of London (QMUL), are approaching AI literacy, governance, and staff development. Many discussions continued well beyond the formal sessions, with requests for future collaboration, advice, and shared learning. These conversations highlighted a common global challenge: while AI tools are advancing rapidly, structured educational frameworks often lag behind.
Several colleagues expressed genuine surprise at how much has already been achieved through the Centre for Excellence in Artificial Intelligence in Education at QMUL on a University-wide basis. In particular, the Centre’s emphasis on ethical governance, pedagogically grounded integration, staff development, and critical AI literacy stood out to international audiences, many of whom highlighted the value of the Centre’s workshops as practical examples of how structured, responsible frameworks for AI adoption can be developed, rather than relying on technology-driven experimentation.
This experience reinforced the importance of institutional leadership in this area. At QMUL, the Centre for Excellence in Artificial Intelligence in Education provides a clear example of how AI can be approached responsibly — with a focus on educational value, ethics, and long-term impact rather than novelty alone. The Centre’s emphasis on critical AI literacy and informed adoption closely reflects the questions being raised internationally.
From my perspective, in an AI-enabled educational environment, future dental curricula are likely to place greater emphasis on clinical reasoning, ethical judgement, and the critical evaluation of digital and AI-supported outputs, rather than on knowledge recall alone. AI may increasingly be used to support educational planning and quality improvement, for example by assisting with pattern recognition and predictive insights that help educators refine curricula, identify areas of learner difficulty at an earlier stage, and provide more timely academic support.
Alongside discipline-specific competencies such as diagnostic interpretation, treatment planning, and safe clinical decision-making, students will also require transferable skills including AI literacy, data awareness, reflective practice, and an understanding of the limitations and risks of automated systems. From an educational perspective, AI-supported tools may assist staff in analysing learner engagement, tailoring teaching materials, and developing accessible resources — such as enhanced visual or video-based content — that support deeper understanding, while maintaining clear academic oversight and responsibility.
These engagements demonstrate not only the growing demand for practical guidance, but also the opportunity — and responsibility — for institutions such as QMUL to support colleagues through structured, ethically grounded educational frameworks and to continue enabling thoughtful leadership in this evolving area.
Dr Ali Nankali
Clinical Reader in Digital Dentistry
https://www.qmul.ac.uk/dentistry/people/profiles/dralinankali.html