Glasgow conference puts AI in dentistry under the clinical spotlight
Artificial intelligence is moving from a speculative add-on to a practical tool in dental care, and this Friday’s Royal College of Surgeons and Physicians of Glasgow annual dental conference is set up around that shift. The programme centers on how AI may influence diagnosis, treatment planning, patient communication, orthodontic monitoring, laboratory workflows and the training of future clinicians.
The agenda is broad, but the clinical question is narrow: where does AI improve care without weakening the judgment, communication and technical skill that still define dentistry?
Professor Falk Schwendicke, Chair and Head of the Clinic for Conservative Dentistry and Periodontology at Ludwig-Maximilians University Munich, will open that discussion with a keynote on the patient impact of AI in dental healthcare. His role on the programme signals a crucial point about the technology: the conversation is no longer limited to algorithms and software architecture. In dentistry, any useful AI platform has to be judged against bedside realities — whether it sharpens detection, supports decisions, or risks adding opacity to processes that already demand precision.
Diagnosis, planning and prediction are the clearest near-term uses
Several speakers will examine how AI could influence the earliest steps in dental care, where pattern recognition and risk stratification are natural fits for machine learning. Professor Patrik Zachrisson, Assistant Professor of Digital Dentistry at the College of Medicine and Dentistry in Birmingham, will address AI-driven treatment planning and predictive patient health, with an emphasis on case management. In practical terms, this is where AI tends to attract the most attention: it can process imaging, records and longitudinal data faster than a clinician can do manually, then surface patterns that may not be obvious at first glance.
The appeal is easy to understand. Dental practice is full of repetitive judgments built on imaging, risk assessment and follow-up decisions. A system that can sort probable findings, compare prior scans or flag cases needing closer review could streamline clinic time and improve consistency. But that same workflow creates pressure points. If the model is opaque, clinicians may struggle to know why a recommendation appears. If the data are incomplete or biased, the output can mislead rather than assist.
One sentence captures the clinical stakes: AI can accelerate decision-making, but it cannot replace responsibility for it.
Saliva data and personalized care raise the bar for precision dentistry
Dr Victoria Sampson, CEO of THS Labs in London, will speak on the intersection between AI, saliva and personalised care. That pairing is especially interesting because saliva sits at the crossroads of diagnostics, prevention and monitoring. If digital tools can interpret salivary biomarkers alongside clinical and radiographic findings, dental teams may gain a more individualized picture of oral health and systemic risk.
The promise here is not abstract. Dentistry has long relied on visual examination, radiographs and clinical history, yet oral disease often evolves over time and across multiple risk factors. AI may help assemble those scattered signals into a more coherent risk profile, especially when the data are longitudinal. Still, personalized care only becomes meaningful if the underlying measurements are reliable and if clinicians can explain the result to patients in plain language. A sophisticated output that cannot be translated into action will not change outcomes.
Communication, workflow and remote monitoring are becoming part of the same conversation
Patient-facing communication will also feature prominently. Dr Morven McCauley, cosmetic implant dentist and partner at Pain Free Dentistry Group, will address how AI diagnostics can enhance patient communication and understanding. In daily practice, this may be one of the most immediate uses of the technology. Dental care often depends on trust, consent and the patient’s willingness to accept treatment recommendations. If AI tools can present findings more clearly, visualize disease progression or help explain why a treatment is needed, they may improve engagement rather than simply increase throughput.
Dr Aman Ulhaq, lead clinician in orthodontics at the Edinburgh Dental Institute, will focus on AI orthodontic workflow and remote monitoring of cases. Orthodontics is a logical setting for this discussion because treatment is iterative and image-driven. Monitoring alignment, tracking progress and identifying deviations from a planned course are tasks that lend themselves to digital support. Remote monitoring can also reduce unnecessary visits when a case is stable, though it introduces a different challenge: clinicians must not let convenience eclipse careful review when symptoms, movement or compliance change unexpectedly.
Training, regulation and professional judgment remain unresolved pressure points
Dr Andrew O’Malley, senior lecturer at the University of St Andrews Medical School and deputy programme director of the Scottish Graduate Entry Medical Programme, will discuss the impact of AI on training, described in the programme as “the good, the bad and the interesting.” That framing fits a profession in transition. If students and junior clinicians rely too heavily on automated prompts, core diagnostic and procedural skills may weaken. If they are trained to interrogate AI critically, the technology could become a powerful supplement to conventional learning.
Dr Janak Gunatilleke, Head of Health Data and Analytics at KPMG, will address the challenges of AI use in dentistry. Those challenges are likely to include governance, data quality, implementation and accountability. Dentistry does not need more digital tools for their own sake; it needs systems that work safely in the real world, across different practices, with different patient populations and different levels of digital maturity.
Stephen Dunn, Lecturer in Dental Technology at the University of Glasgow, will round out the technical discussion with a session on AI and digital dentistry: bridging clinic and laboratory. That link matters because restoration design, fabrication and chairside fit increasingly depend on digital workflows. When the clinic and lab operate from the same data stream, turnaround may improve and errors may fall. When those systems do not communicate cleanly, the result can be delay, rework and lost confidence on both sides of the handoff.
The conference offers six hours of continuing professional development, but its broader significance is larger than a CPD certificate. It reflects a profession testing how far AI can go before it starts to compete with clinical judgment rather than support it. The programme asks a practical question: which parts of dentistry can be made more accurate, more efficient or more understandable with AI, and which parts should remain firmly in the hands of the clinician?
A poster competition will also give delegates a chance to present work to peers, extending the conversation beyond plenary talks. In a field where technology is moving quickly, that kind of exchange may prove as valuable as any keynote. The unanswered issue is not whether AI will enter dentistry, but how carefully the profession will define its role before it becomes embedded in everyday practice.