From passive adoption to responsible use of AI in dentistry

Dr Ali Nankali

Wed. 30 September 2026

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Ask a group of dentists whether they use artificial intelligence (AI) in their clinical practice, and you will get a wide range of answers. Some will say they use it regularly; others are interested but have not yet begun using it. Some will say they do not use AI at all—yet they may already be working with AI-supported technology every day without recognising it as such.

This reflects the way AI is entering dentistry. Unlike previous technological shifts, AI is not arriving as one identifiable piece of equipment that a dentist consciously chooses to adopt. It is increasingly embedded in imaging and diagnostic software, digital treatment planning systems, automated design tools, administrative applications and communication platforms. AI applications are already being explored across diagnosis, image analysis, treatment planning and record-keeping.^1, 2 The more important question, then, may not be simply whether dentists are adopting AI, but how they are learning about it, how they interpret its outputs and how confidently and responsibly they are using it.

Through my work in dental education and clinical practice, attendance at professional events and conversations with international colleagues, I see two broad routes through which dentists are currently engaging with AI. I call these passive adoption and active adoption. In practice, these pathways often overlap, and passive exposure may be the starting point for more active engagement.

Passive adoption: Using AI without necessarily seeking it out

Passive adoption happens when AI enters dentists’ working environments through technology they already use. Think about the evolution of the digital dental clinic. Dentists may already work with digital radiography, intra-oral scanning, CBCT, CAD/CAM, digital treatment planning and practice management software. As these platforms develop, increasingly sophisticated algorithms and AI-supported functions are being built into existing workflows. Clinicians may therefore benefit from automated image analysis, anatomical recognition, segmentation, treatment planning assistance or intelligent design without ever making a conscious decision to start using AI. It simply becomes another layer within the digital system they already rely on.

This is worth noting because it is a change from the usual model of technological adoption in dentistry. When practices moved from physical impressions to intra-oral scanners, for example, the shift was difficult to miss. Equipment had to be purchased, staff had to be trained and workflows had to change. By contrast, the transition to AI can be far less visible.

Manufacturers are playing a significant role here. Established digital platforms are introducing greater levels of automation into imaging, planning and restorative workflows. This reflects a wider industry trend: as software becomes more sophisticated, clinicians may find themselves working with increasingly intelligent systems regardless of whether they think of themselves as early AI adopters.

“Unlike previous technological shifts, AI is not arriving as one identifiable piece of equipment that a dentist consciously chooses to adopt.”

The potential here is real. AI approaches have been explored for dental image analysis, treatment outcome prediction, treatment planning and clinical decision support.^1, 2 Used well, these tools can contribute to efficiency, consistency and the handling of complex digital information.

However, using an AI-supported function is not the same as understanding it. A clinician may be perfectly comfortable operating a system without knowing what data the algorithm used, how it generated the output, where its limitations lie or when to question the result. The difference between using AI and understanding it will only become more important as AI becomes less visible in the technologies we use.

Active adoption: Choosing to understand AI

The second pathway looks quite different. Some dentists are deliberately seeking out greater knowledge of AI and advanced digital dentistry. They attend courses, lectures, conferences and exhibitions. They discuss technologies with colleagues, watch demonstrations, compare systems and ask how these developments might affect their own practice.

Their motivations vary. Some clinicians are naturally drawn to technology. Others have experienced the benefits of digital workflows and want to go further. Some simply recognise that dentistry is changing and do not want to fall behind the technology they work with. Others have seen what a colleague or another practice can do and have become curious.

Research involving dental students and specialty trainees suggests broadly positive attitudes towards AI—but also significant gaps in knowledge and structured education.³ Although students and established practitioners are different populations, the broader point still holds: access to AI is advancing faster than professional understanding of it. This is why I think that education has an increasingly important role to play. A focused course can provide structured learning on a specific subject. However, from what I have seen, conferences and broader innovation events offer something different—particularly in a field that is evolving so quickly.

At a conference, clinicians can encounter several technologies in a single day. They can compare systems side by side, hear from colleagues who use them, speak directly with manufacturers, discuss real-world problems and begin to distinguish genuine clinical value from a polished demonstration. That ability to evaluate AI more comprehensively matters.

When different approaches are brought together in the same professional setting, comparison becomes more natural and the questions tend to become sharper. I have observed this through my involvement in organising the Advanced Dentistry & Innovation Conference & Exhibition in London through UKDentalCourses. Discussions at the event have also reinforced my impression that interest in AI and digital dentistry extends well beyond individual markets and is increasingly part of an international professional conversation. Dentists in different countries are asking strikingly similar questions: What can this technology actually do? How reliable is it? Which system suits my practice? How much should I trust the output? What happens if the AI is wrong? And perhaps most importantly: who is responsible for the final decision?

Moving from access to understanding

These questions reveal why AI education should not focus solely on demonstrating what the technology can do. It should also address interpretation. A common comment I hear when discussing AI with colleagues is some version of: “I tried it, but it gave me the wrong answer.” That reaction deserves more consideration than simply dismissing AI as unreliable.

AI systems can certainly produce inaccurate, incomplete or inappropriate outputs—which is precisely why professional oversight matters. But there is another side to this: the quality of an AI output often depends heavily on the quality and completeness of the information provided to it.

Humans communicate with a great deal of assumed context. Two dentists discussing a clinical case understand many things without stating them explicitly because they can draw on shared professional knowledge and experience and on the broader contextual understanding that comes from human experience. An AI system does not automatically have access to that same context. Learning to use AI well, then, involves learning to communicate with it more precisely: defining the problem clearly, providing appropriate context, questioning the response and verifying anything important.

There is also a meaningful difference between asking AI for an answer and using it to support the clinician’s thinking. Rather than asking, “What should I do with this patient?”, a more professional approach might be for the clinician to provide relevant anonymised information, ask the system to identify key considerations or alternative approaches, examine its reasoning, challenge its assumptions and then weigh the output against clinical judgement and the available evidence.

The final decision remains the clinician’s. This matters especially in healthcare. The World Health Organization’s guidance on AI for health emphasises human autonomy, transparency, accountability and safety, as well as the need for AI to be governed in ways that genuinely protect patients.⁴ For dentistry, AI literacy should not simply mean knowing how to operate a tool. It must also include knowing when to question it.

The dentist remains part of the system

Perhaps the most persistent misunderstanding about AI is that it is primarily about replacing professionals. I see the immediate reality differently. The most useful AI applications in dentistry are likely to be those in which technology and professional judgement work together. AI can process information quickly, recognise patterns, organise documentation, generate alternatives or flag something that warrants a closer look. The dentist brings clinical context, experience, ethical judgement, knowledge of the individual patient and responsibility for the outcome.

The idea of AI augmenting rather than replacing healthcare professionals is already recognised in the dental literature.² That also changes how dentists should be educated about AI. We do not need every dentist to understand machine learning architecture or the mathematics behind a neural network. Most clinicians do not understand the engineering behind every piece of equipment they use, and that is fine. However, they do need enough understanding to ask the right professional questions.

“Using an AI-supported function is not the same as understanding it.”

What does this system actually do? What evidence supports it? What information does it need from me? What happens to the data I provide? What are its known limitations? Can I explain its role to my patient? When should I set aside its recommendation? Am I ready to take professional responsibility for the decision based on it? I believe that these questions are becoming central to the responsible use of AI in dentistry.

A gap the profession needs to address

Passive adoption will almost certainly continue as digital systems become more sophisticated and AI-supported functions are increasingly integrated into everyday workflows. There is nothing inherently wrong with that. Good technology should make complex processes easier to navigate.

The concern arises when the pace of adoption outstrips the pace of professional understanding. The greater risk may not be that dentists refuse to use AI, but that they use it without developing a meaningful understanding of what it is doing, where its limitations lie and when its output should be questioned.

Addressing that gap will require contributions from educators, professional organisations, manufacturers, event organisers and professional publications. Each can help clinicians understand emerging technologies, compare approaches, examine their limitations and make informed choices about their use in practice.

The goal should not be to persuade every dentist to adopt every new technology. It should be to help clinicians decide which technologies are useful, appropriate and sufficiently well understood to support patient care.

From passive adoption to informed engagement

The profession should avoid two extremes: uncritical enthusiasm, where every new AI development is treated as progress simply because it is new, and automatic dismissal, where potentially useful technology is rejected because it is unfamiliar or imperfect. The position dental professionals should take lies between these extremes: curiosity combined with critical judgement.

AI should be tested, questioned and understood. Its limitations should be discussed as openly as its benefits, and clinicians should remain willing to disregard an AI recommendation when their professional judgement and the evidence point elsewhere.

The future divide within the profession may therefore not be between dentists who use AI and those who do not. It may be between those who encounter it passively and those who make the effort to understand, question and use it responsibly.

AI does not remove the need for dentists to think. If anything, it makes critical thinking more important than ever. As the technology develops, our responsibility as dental professionals is to develop alongside it by ensuring that human judgement continues to guide its use in patient care.

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