# International Perspectives on Digital and Generative AI Adoption and Governance in Undergraduate Dental Education: A Cross-Sectional Survey

## TL;DR

This study explores how digital tools and generative AI are used in dental education worldwide, finding uneven adoption and a lack of governance.

## Contribution

The study provides a cross-national survey of digital and AI adoption in dental education, highlighting governance gaps.

## Key findings

- Digital tools like videoconferencing and LMS are widely adopted, but clinical records remain paper-based in 32% of institutions.
- Generative AI is commonly used, but formal institutional guidance is often absent.
- Adoption of simulation and 3D printing technologies is inconsistent across institutions.

## Abstract

Background/Objectives: Digital technologies and generative artificial intelligence (AI) are increasingly used in undergraduate dental education, yet international variations in adoption and governance remain insufficiently described. This study aimed to characterise cross-national patterns of educational software use, perceived importance for curriculum delivery, and institutional readiness for AI governance. Methods: A cross-sectional online survey of educators and academic administrators involved in undergraduate dental education captured institutional software use across teaching delivery, learning management, assessment, clinical record systems, imaging, simulation, digital workflows, and generative AI. Results: A total of 97 respondents from 38 countries completed the survey, with most institutions delivering both undergraduate and postgraduate dental education (66.0%). Videoconferencing platforms were widely adopted. LMS provision varied, with Google Classroom, Moodle, and Blackboard most frequently reported. Paper-based clinical records remained in use in 32% of institutions. Among digital PMS/EDR platforms, axiUm, Salud/Titanium, and Carestream Dental were the most prevalent. Adoption of simulation software, CAD/CAM systems, and 3D printing was inconsistent. LMS and videoconferencing were most often rated as essential, whereas simulation, scanners, CAD/CAM, and 3D printing were generally considered useful but not essential. Generative AI use was commonly reported, while formal institutional guidance and policies were frequently absent. Conclusions: Although digital integration in undergraduate dental education is widespread, its distribution is uneven across different regions and technology domains. The combination of rapid generative AI uptake and limited governance highlights an urgent need for institution-level guidance, staff development, and strategic investment to support responsible and equitable integration.