Use of Artificial Intelligence among Dental Clinicians and Oral and Maxillofacial Surgeons: A Cross-Sectional Survey

Abstract

Objective: To evaluate the utilization, knowledge, and attitudes of dental clinicians and oral/maxillofacial surgeons regarding AI in clinical practice. Study Design and Setting: A Cross-Sectional Online Survey. Methodology: The study was conducted over six months on 303 participants using a non-probability consecutive sampling technique. Participants were recruited via digital platforms. A structured, 21-item questionnaire, adapted from a validated tool, was distributed through online professional networks. Data were analyzed using SPSS v21, employing descriptive statistics and inferential tests (chi-square) to explore associations, with a significance threshold of p < 0.05. Results: A total of 70% of participants were aged 18–25, with the majority still in training or having less than five years of experience. General Dentistry was the most represented specialty (60.1%), and 81.5% practiced in urban areas. AI usage was limited, with 42.6% reporting no use in daily practice; radiographic interpretation was the most common application (25.8%). A significant association was found between specialty and AI usage (p = 0.023) and between experience and AI knowledge (p < 0.001), while no significant link was observed with age or work area. Conclusion: the growing awareness and cautious optimism toward AI among Pakistani dental professionals, particularly among younger and early-career clinicians. While AI use remains limited, there is strong recognition of its potential to enhance diagnostics and efficiency. Differences in AI adoption across specialties and experience levels underscore the need for targeted education and infrastructure development to support broader integration.

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