Currently submitted to: JMIR Human Factors
Date Submitted: Jun 12, 2026
Open Peer Review Period: Jun 25, 2026 - Aug 20, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Evolution of Dental Students’ Perceptions of Artificial Intelligence in Dental Education: A Comparative Cross-Sectional Survey Study From 2025 to 2026
ABSTRACT
Background:
Background:
Artificial intelligence (AI) is increasingly influencing dental education, clinical decision-making, diagnostics, and treatment planning. However, the evolution of dental students’ perceptions over time remains insufficiently explored, particularly among international students enrolled in English-language dental programs.
Objective:
Objective:
This study aimed to compare perceptions, usage patterns, perceived benefits, concerns, and educational expectations regarding AI among third-year dental students surveyed in 2025 and 2026.
Methods:
Methods:
Two anonymous cross-sectional questionnaire surveys were conducted among independent cohorts of third-year undergraduate dental students enrolled in an English-language dental medicine program. The same questionnaire was administered in both years. The 2025 cohort included 109 respondents, and the 2026 cohort included 92 respondents. Collected demographic variables included gender, age, and country of origin. Categorical variables were compared using chi-square tests, and ordinal responses were additionally analyzed using Mann–Whitney U tests. Statistical significance was set at P<.05.
Results:
Results:
A total of 201 students participated. Reported frequent AI use increased from 22 of 109 students (20.2%) in 2025 to 27 of 92 students (29%) in 2026, while “rarely or never” responses decreased from 35 of 109 students (32.1%) to 19 of 92 students (21%). Ordinal comparison indicated a statistically significant increase in frequency of AI use between the two cohorts (Mann–Whitney U=4243.5; P=.04). Perceived benefits also shifted significantly (χ²₃=8.27; P=.04), with “improved treatment planning” increasing from 13 of 109 students (11.9%) in 2025 to 24 of 92 students (26%) in 2026. Familiarity with regulations and legal guidelines remained limited: 68 of 109 students (62.4%) in 2025 and 46 of 92 students (50%) in 2026 reported being “not familiar” with such guidelines. Perceived institutional preparedness remained low, with 69 of 109 students (63.3%) in 2025 and 62 of 92 students (67%) in 2026 reporting that their institution did not provide sufficient AI-related training
Conclusions:
Conclusions:
Between 2025 and 2026, third-year dental students demonstrated a measurable shift toward more frequent AI use and a stronger perception of AI as a tool for treatment planning. However, ethical, legal, and institutional training gaps persisted. These findings support the need for structured AI literacy, regulatory awareness, and clinically oriented AI training within dental curricula.
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