Embodied AI in dentistry: From diagnosis to action

Dental Tribune International

Wed. 14. October 2026

save

GUANGZHOU, China: Artificial intelligence (AI) has already demonstrated substantial utility in dentistry. Researchers are now exploring whether it could also help dentists manage the challenges of working in the oral cavity. A new narrative review has examined how embodied artificial intelligence (EAI), which combines AI with sensory technologies and robotics, could serve as a clinician-supervised co-pilot during clinical procedures. The review identified promising technological developments.

Drawing on dental, medical and engineering literature, the researchers examined the technologies needed to enable EAI systems and their potential clinical applications. They organised their review around four interconnected functions: gathering information from the clinical environment, integrating it with patient information and existing knowledge, planning interventions and guiding their physical execution.

An important requirement for EAI is the ability to collect reliable information in the oral cavity. The review highlighted research into force and haptic sensing technologies that enable robotic systems to detect changes in mechanical resistance during implant procedures, potentially supporting anatomical landmark detection and assessment of primary stability. Other developments include robotic systems using optical tracking to compensate for simulated patient movements and orthodontic aligners that measure occlusal forces for treatment monitoring.

EAI systems would also need to draw on patient histories and existing clinical knowledge to inform decisions. The review highlighted research into AI models capable of processing different types of dental information, as well as datasets containing findings from repeated examinations and follow-up visits. The researchers also discussed approaches developed for general robotic surgery that could enable EAI systems to learn from previous procedures and apply that knowledge to clinical decisions.

In AI-assisted treatment planning, studies have investigated systems that use bone anatomy and prosthetic requirements to generate implant placement plans, including for zygomatic implant procedures. The researchers also discussed how digital twins could be used to simulate different treatment scenarios and anticipate possible outcomes.

Regarding the physical execution of procedures, the review described robotic systems that can guide instruments along planned paths and use information from sensors to adjust their movements. Studies of robot-assisted endodontic microsurgery have reported promising accuracy in laboratory testing, and small clinical case series have provided early evidence of applicability.

Developments in dental robotics have attracted particular attention recently. A scoping review, for example, found high implant placement accuracy with robotic systems. Dental Tribune International has reported a full-arch rehabilitation case involving robotic implant placement and laboratory research demonstrating improved accuracy in preparing recipient sockets for tooth autotransplantation using a robot.

The review researchers reported that much of the existing evidence comes from engineering studies, in vitro experiments, preclinical simulations and limited clinical series, but that there are relatively few prospective comparative or long-term clinical studies. Some approaches have also been developed in other fields, and their applicability to dentistry is uncertain. Consequently, although technical feasibility has been demonstrated in some areas, the evidence to date is insufficient to establish the clinical effectiveness and long-term safety of integrated EAI systems.

The article, titled “The prospect of embodied intelligence in dentistry”, was published online in the December 2026 issue of the International Dental Journal.