Utilization of Artificial Intelligence Tools in Dentistry and Its Perception Among Dental Students: A Cross-Sectional Study

Abstract

Introduction: Artificial intelligence (AI) refers to computational systems capable of performing tasks that traditionally require human intelligence, such as natural language processing, pattern recognition, and decision support. In recent years, AI tools—particularly large language models (LLMs) such as ChatGPT, Google Gemini, and Microsoft Copilot—have increasingly influenced educational processes and clinical workflows across healthcare professions, including dentistry. Therefore, this study aims to assess the utilization of diverse AI tools available to dental students and to evaluate their awareness, perceptions, and attitudes toward incorporating these technologies into dental education and future clinical practice.

Materials & Methods: A cross-sectional questionnaire-based study was conducted among 408 dental students (336 BDS and 72 MDS) in a private dental college. A validated, self-administered questionnaire assessed sociodemographic details, awareness, utilization, and perceptions of AI tools. The questionnaire demonstrated good content validity (CVI = 0.89) and internal consistency (Cronbach’s alpha = 0.82). Descriptive and inferential statistics were applied, and p < 0.05 was considered statistically significant.

Results: Overall awareness of AI tools was high, with ChatGPT being the most recognized platform (89.9% BDS; 97.2% MDS). MDS students demonstrated significantly higher awareness of most AI tools compared to BDS students (p < 0.05). AI utilization was predominantly academic, including learning, examination preparation, literature search, and research writing. Clinical decision-support usage was comparatively low but significantly higher among MDS students (22.2%) than BDS students (7.7%) (p < 0.001). Perceptions toward AI were generally positive, with a majority agreeing that AI enhances learning efficiency (75.0% BDS; 88.9% MDS). Ethical concerns were reported by both groups, more frequently among BDS students (66.7%). Composite scores for awareness, utilization, and perception were significantly higher among MDS students (p < 0.001).

Conclusion: Dental students exhibited high awareness and favourable perceptions of AI tools, with utilization primarily focused on academic and research purposes. Postgraduate students demonstrated greater engagement and more positive attitudes than undergraduates. Structured incorporation of AI literacy, ethical guidance, and supervised clinical integration into dental curricula is recommended to ensure responsible and effective adoption of AI technologies.