ArticleBMC medical education2025
Exploring dental faculty awareness, knowledge, and attitudes toward AI integration in education and practice: a mixed-method study.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of artificial intelligence in endodontic education: a systematic review.Frontiers in dental medicine · 2026Pooled it
- Responsible Clinical AI in Dentistry: Trust, Professional Autonomy, and Perceptions of Accountability Across Stakeholders in Romania-A Multidisciplinary Cross-Sectional Survey.Healthcare (Basel, Switzerland) · 2026Article
- AI-informed healthcare pedagogy: a review of the literature and application to pedagogical practice informed by case studies from dental education.British dental journal · 2026Review
- Bridging Borders, Bridging Barriers: Artificial Intelligence for Dental Education.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Influence of Oral and Maxillofacial Radiology Training and Experience on Attitudes Toward Artificial Intelligence in Dentistry: A Cross-Sectional Questionnaire Study.Healthcare (Basel, Switzerland) · 2026Article
- A Blended Course for Dental Faculty Development in Educational Design and Digital Teaching Practices.Journal of dental education · 2026Article
- Development and validation of the Dental Artificial Intelligence Readiness and Acceptance Instrument (DAI-RAI) for dental professionals.BMC oral health · 2026Article
- Factors influencing large language model adoption among dental students: a cross-sectional study.Scientific reports · 2026Article
- Exploring Senior Dental Students' Readiness and Perceptions of Artificial Intelligence in Dentistry: Insights From a Cross-Sectional Study.International journal of dentistry · 2026Article
- Artificial intelligence for teaching, training, and assessment in dental education: a domain-based scoping review.Frontiers in medicine · 2026Review
- Clinician-Led Development and Feasibility of a Neural Network for Assessing 3D Dental Cavity Preparations Assisted by Conversational AI.Dentistry journal · 2025Article
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- Artificial Intelligence in Dental Education: A Scoping Review of Applications, Challenges, and Gaps.Dentistry journal · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDentistry is shifting from traditional to digital practices owing to the rapid development of "artificial intelligence" (AI) technology in healthcare systems. The dental curriculum lacks the integration of emerging technologies such as AI, which could prepare students for the evolving demands of modern dental practice. This study aimed to assess dental faculty members' knowledge, awareness, and attitudes toward AI and provide consensus-based recommendations for increasing the adoption of AI in dental education and dental practice.
methodThis mixed-method study was conducted via a modified version of the General Attitudes toward Artificial Intelligence Scale (GAAIS) and Focus Group Discussions (FGD). Four hundred faculty members from both public and private dental colleges in Pakistan participated. The quantitative data were analyzed using SPSS version 23. Otter.ai was used to transcribe the data, followed by thematic analysis to generate codes, themes, and subthemes.
resultsThe majority of the faculty members was aware of the application of AI in daily life and learned about AI mainly from their colleagues and social media. Fewer than 20% of faculty members were aware of terms such as machine learning and deep learning. 81% of the participants acknowledged the need for and limited opportunities to learn about AI. Overall, the dental faculty demonstrated a generally positive attitude toward AI, with a mean score of 3.5 (SD ± 0.61). The benefits of AI in dentistry, the role of AI in dental education and research, and barriers to AI adoption and recommendations for AI integration in dentistry were the main themes identified from the FGD.
conclusionsThe dental faculty members showed general awareness and positive attitudes toward AI; however, their knowledge regarding advanced AI concepts such as machine learning and deep learning was limited. The major barriers identified in AI adoption are financial constraints, a lack of AI training, and ethical concerns for data management and academics. There is a need for targeted education initiatives, interdisciplinary and multi-institutional collaborations, the promotion of local manufacturing of such technologies, and robust policy initiatives by the governing body.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.