Dentists' perception of Artificial Intelligence in Clinical Dentistry: a cross-sectional study in Karachi, Pakistan
Abstract
Introduction: Artificial intelligence (AI) is increasingly transforming clinical dentistry by supporting diagnostic assessment, treatment planning, workflow optimization, and patient management. Objective: To assess knowledge, perceptions, attitudes, and concerns of dentists regarding the application of artificial intelligence in clinical dentistry and its perceived impact on oral health, treatment quality, and the dentist–patient relationship. Methodology: An analytical cross-sectional study was conducted from March to August 2024, among 118 dentists from dental institutions and private clinics of Karachi, Pakistan. A structured questionnaire was used to collect demographic data, prior dental care experiences with AI, knowledge and digital awareness, perceived pros and cons, as well as experiences regarding the potential impact of AI on oral health, treatment quality and dentist–patient relationship. Descriptive statistics were used for data analysis and p<0.05 was considered statistically significant. Results: Of 118 participants, 61.0% had an average understanding of AI while 72.0% had an average understanding of the digital world. About 50.8% thought AI helped in enhancing oral health and 41.5% believed it enhanced treatment quality. Data security (18.6%), new challenges for doctors and patients (17.8%) and workforce implications (16.1%) were commonly reported concerns. The most common perceived benefit was a good doctor–patient relationship (35.6%). Perceived importance of oral health (p=0.021), previous dental treatment (p=0.035), AI related concerns (p=0.029), advantages of AI (p=0.015), improvement in treatment quality (p=0.026) and oral health (p=0.018) were statistically significant. Conclusion: The perceptions of dentists regarding AI were generally positive, with a cautious stance toward the use of AI in clinical dentistry. The results highlight the necessity for systematic education about AI, hands-on experience and robust data security systems to facilitate responsible integration in clinical practice.