From lecture hall to clinic: dental students' AI readiness and anxiety across educational stages

Although artificial intelligence (AI) is increasingly shaping modern healthcare, its integration into dental education remains underexplored-particularly with regard to how students' readiness and anxiety toward AI evolve throughout their academic progression. Existing studies primarily focus on medical cohorts, leaving a critical knowledge gap in understanding how dental students across different years perceive and adapt to these technological transformations. This study aims to address this gap by assessing both cognitive readiness and emotional responses to AI among current and future dental professionals.

A cross-sectional survey was conducted with 420 participants, including first- to fifth-year dental students and recent graduates, using purposive sampling. Two validated instruments were employed: the Medical Artificial Intelligence Readiness Scale and the Artificial Intelligence Anxiety Scale. Descriptive statistics and one-way ANOVA were used to analyze differences across academic year, gender, age, AI familiarity, and prior training experience.

Significant differences in AI readiness were observed based on academic year, with second-year students demonstrating the highest readiness across subdomains (Cognition, Ability, Vision), while fifth-year students scored the lowest. Participants with prior AI-related knowledge or training consistently showed higher readiness and lower anxiety levels, although the reduction in anxiety was not always statistically significant. Gender-based analysis revealed that female participants reported higher AI anxiety in specific subdomains, including Learning and Surveillance, while overall readiness scores did not significantly differ by gender or age.

Findings emphasize the need for early, continuous, and practice-oriented AI education in dental curricula. Structured exposure to AI-related concepts not only enhances competence but may also reduce anxiety. Tailoring pedagogical approaches to different stages of training could foster a more balanced integration of AI in dentistry-addressing both technological proficiency and emotional resilience.