review_article October 9, 2026

Applications of Generative Artificial Intelligence in Dental and Orthodontic Education: A Systematic Review of Opportunities, Challenges, and Future Perspectives

Mahdi Hossaini, Hamidullah Najm
Volume1
Issue4
Pages71-84
DOI10.5281/zenodo.23283890
Abstract

Generative artificial intelligence (AI) has rapidly been introduced in medical and dental education, creating opportunities for students in how to learn and engage with educational content. Through its ability to generate educational content, deliver immediate feedback, simulate clinical situations, and support individual learning, generative AI has the potential to reshape conventional approaches to dental and orthodontic education.
This systematic review aimed to examine the applications of generative AI in dental and orthodontic education and to evaluate its educational opportunities, challenges, and outcomes, with particular emphasis on learning and knowledge retention, clinical decision-making, practical skills, educational assessment, and feedback. A systematic review was conducted using the PICO framework and in accordance with PRISMA guidelines. Major scientific databases, including PubMed, Cochrane Library, ERIC, CINAHL, IEEE Xplore, ISI, ISC, and Magiran, were systematically searched for studies published between 2010 and 2024. After screening and eligibility assessment, 17 studies were included in the qualitative synthesis. Risk of bias and certainty of evidence were evaluated using appropriate methodological assessment tools.
The review studies mentioned that AI-based educational tools may enhance student engagement, learning, and selected clinical competencies through personalized learning, immediate feedback, educational chatbots, and simulated learning environments. AI tools also excelled at answering specialized dental and orthodontic questions and supporting students in making clinical decisions. However, the evidence also highlights important concerns regarding the accuracy and reliability of AI-generated outputs, data privacy, algorithmic transparency, excessive reliance on AI, faculty preparedness, and limitations in technical infrastructure.
Generative AI can generate a textbook orthodontic treatment plan in seconds, but it cannot teach a student how to calm a terrified patient sitting in the dental chair. We have to explicitly protect time for chairside manner, active listening, and human connection.

Keywords
Generative artificial intelligenceDental educationOrthodontic educationPersonalized learningClinical decision-makingEducational assessmentArtificial intelligence.
Download Article PDF
References
  1. Bragazzi, N. L., & Garbarino, S. (2024). Toward clinical generative AI: Conceptual framework. JMIR AI, *3*, e55957. https://doi.org/10.2196/55957
  2. Carroll, A. J., & Borycz, J. (2024). Integrating large language models and generative artificial intelligence tools into information literacy instruction. Journal of Academic Librarianship, *50*(4), 102899.
  3. Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, *20*(1), 43. https://doi.org/10.1186/s41239-023-00411-8
  4. Chau, R. C. W., Thu, K. M., Yu, O. Y., Hsung, R. T. C., Lo, E. C. M., & Lam, W. Y. H. (2024). Performance of generative artificial intelligence in dental licensing examinations. International Dental Journal, *74*(3), 616–621. https://doi.org/10.1016/j.identj.2023.12.007
  5. Chen, Y., & Esmaeilzadeh, P. (2024). Generative AI in medical practice: In-depth exploration of privacy and security challenges. Journal of Medical Internet Research, *26*, e53008. https://doi.org/10.2196/53008
  6. Cochrane Training. (2024). GRADE approach: Grading the certainty of evidence. Cochrane.
  7. Cook, M. (2024). The lifecycle of 3D data in academic libraries: A survey of methods and implications for information professionals. Journal of Academic Librarianship, *50*(5), 102933. https://doi.org/10.1016/j.acalib.2024.102933
  8. Daraqel, B., Wafaie, K., Mohammed, H., Cao, L., Mheissen, S., Liu, Y., & et al. (2024). The performance of artificial intelligence models in generating responses to general orthodontic questions: ChatGPT vs Google Bard. American Journal of Orthodontics and Dentofacial Orthopedics, *165*(6), 652–662. https://doi.org/10.1016/j.ajodo.2024.01.012
  9. Dixon, J. (2021). Improving the quality of care in health systems: Towards better strategies. Israel Journal of Health Policy Research, *10*, 15. https://doi.org/10.1186/s13584-021-00448-y
  10. Duggal, I., & Tripathi, T. (2024). Ethical principles in dental healthcare: Relevance in the current technological era of artificial intelligence. Journal of Oral Biology and Craniofacial Research, *14*(3), 317–321. https://doi.org/10.1016/j.jobcr.2024.04.003
  11. Fang, Q., Reynaldi, R., Araminta, A. S., Kamal, I., Saini, P., Afshari, F. S., Tan, S. C., Yuan, J. C., Qomariyah, N. N., & Sukotjo, C. (2025). Artificial intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning environment. Journal of Prosthetic Dentistry, *134*(4), 1296–1303. https://doi.org/10.1016/j.prosdent.2024.03.038
  12. Gandedkar, N. H., Wong, M. T., & Darendeliler, M. A. (2021). Role of virtual reality (VR), augmented reality (AR) and artificial intelligence (AI) in tertiary education and research of orthodontics: An insight. Seminars in Orthodontics, *27*(2), 69–77. https://doi.org/10.1053/j.sodo.2021.05.003
  13. Ghorashi, N., Ismail, A., Ghosh, P., Sidawy, A., & Javan, R. (2023). AI-powered chatbots in medical education: Potential applications and implications. Cureus, *15*(8), e43271. https://doi.org/10.7759/cureus.43271
  14. Giordano, C., Brennan, M., Mohamed, B., Rashidi, P., Modave, F., & Tighe, P. (2021). Accessing artificial intelligence for clinical decision-making. Frontiers in Digital Health, *3*, 645232. https://doi.org/10.3389/fdgth.2021.645232
  15. Gupta, P., Ding, B., Guan, C., & Ding, D. (2024). Generative AI: A systematic review using topic modelling techniques. Data and Information Management, *8*(2), 100066.
  16. Haase, J., & Hanel, P. H. P. (2023). Artificial muses: Generative artificial intelligence chatbots have risen to human-level creativity. Journal of Creativity, *33*(3), 100066.
  17. Higgins, J. P. T., Savović, J., Page, M. J., Elbers, R. G., & Sterne, J. A. C. (2022). Assessing risk of bias in a randomized trial. In J. P. T. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li, M. J. Page, & V. A. Welch (Eds.), Cochrane handbook for systematic reviews of interventions (Version 6.3, Chapter 8). Cochrane.
  18. Karabacak, M., Ozkara, B. B., Margetis, K., Wintermark, M., & Bisdas, S. (2023). The advent of generative language models in medical education. JMIR Medical Education, *9*, e48163. https://doi.org/10.2196/48163
  19. Karanth, D., Abu Arqub, S., & Dolce, C. (2024). The applications of digital technology in postgraduate orthodontic education. Seminars in Orthodontics, *30*(4), 436–442. https://doi.org/10.1053/j.sodo.2024.03.003
  20. Larson, B. Z., Moser, C., Caza, A., Muehlfeld, K., & Colombo, L. A. (2024). Critical thinking in the age of generative AI. Academy of Management Learning & Education, *23*(3), 373–378. https://doi.org/10.5465/amle.2024.0338
  21. Lin, L., Tang, B., Cao, L., Yan, J., Zhao, T., Hua, F., & et al. (2023). The knowledge, experience, and attitude on artificial intelligence-assisted cephalometric analysis: Survey of orthodontists and orthodontic students. American Journal of Orthodontics and Dentofacial Orthopedics, *164*(4), e97–e105. https://doi.org/10.1016/j.ajodo.2023.07.006
  22. Liu, J., Zhang, C., & Shan, Z. (2023). Application of artificial intelligence in orthodontics: Current state and future perspectives. Healthcare, *11*(20), 2760. https://doi.org/10.3390/healthcare11202760
  23. Mengi, A., Singh, R. P., Mengi, N., Kalgotra, S., & Singh, A. (2024). A questionnaire study regarding knowledge, attitude and usage of artificial intelligence and machine learning by the orthodontic fraternity of Northern India. Journal of Oral Biology and Craniofacial Research, *14*(5), 500–506.
  24. Miramadi, S. E., et al. (2024). Generative artificial intelligence: Multidisciplinary perspectives on opportunities, challenges, and implications in research, practice, and policymaking. Science and Technology Policy, *17*, 1–100.
  25. Nordblom, N. F., Büttner, M., & Schwendicke, F. (2024). Artificial intelligence in orthodontics: Critical review. Journal of Dental Research, *103*(6), 577–584. https://doi.org/10.1177/00220345241235606
  26. Pedersen, I. (2023). The rise of generative AI and enculturating AI writing in postsecondary education. Frontiers in Artificial Intelligence, *6*, 1259407. https://doi.org/10.3389/frai.2023.1259407
  27. Reddy, S. (2024). Generative AI in healthcare: An implementation science informed translational path on application, integration and governance. Implementation Science, *19*, 27. https://doi.org/10.1186/s13012-024-01357-9
  28. Schwendicke, F., Chaurasia, A., Wiegand, T., Uribe, S. E., Fontana, M., Akota, I., Tryfonos, O., Krois, J., & IADR e-oral health network and the ITU/WHO Focus Group AI for Health. (2023). Artificial intelligence for oral and dental healthcare: Core education curriculum. Journal of Dentistry, *128*, 104363. https://doi.org/10.1016/j.jdent.2022.104363
  29. Schwendicke, F., Samek, W., & Krois, J. (2020). Artificial intelligence in dentistry: Chances and challenges. Journal of Dental Research, *99*(7), 769–774. https://doi.org/10.1177/0022034520915714
  30. Sridharan, K., & Sequeira, R. P. (2024). Artificial intelligence and medical education: Application in classroom instruction and student assessment using a pharmacology and therapeutics case study. BMC Medical Education, *24*, 431. https://doi.org/10.1186/s12909-024-05365-7
  31. Surlari, Z., Budală, D. G., Lupu, C. I., Stelea, C. G., Butnaru, O. M., & Luchian, I. (2023). Current progress and challenges of using artificial intelligence in clinical dentistry: A narrative review. Journal of Clinical Medicine, *12*(23), 7378. https://doi.org/10.3390/jcm12237378
  32. Taghizadeh, M., & Khordmandnia, S. (2024). Generative artificial intelligence: Challenges and requirements for development and implementation (Serial No. 19879). Research Center of the Islamic Consultative Assembly.
  33. Thurzo, A., Urbanová, W., Novák, B., Czako, L., Siebert, T., Stano, P., Mareková, S., Fountoulaki, G., Kosnáčová, H., & Varga, I. (2022). Where is the artificial intelligence applied in dentistry? Systematic review and literature analysis. Healthcare, *10*(7), 1269. https://doi.org/10.3390/healthcare10071269
  34. Wells, G. A., Shea, B., O'Connell, D., Peterson, J., Welch, V., Losos, M., & Tugwell, P. (2024). The Newcastle–Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Hospital Research Institute.
  35. Xu, Y., Jiang, Z., Ting, D. S. W., Kow, A. W. C., Bello, F., Car, J., & et al. (2024). Medical education and physician training in the era of artificial intelligence. Singapore Medical Journal, *65*(3), 159–166. https://doi.org/10.4103/singaporemedj.SMJ-2023-203
  36. Yadalam, P. K., Anegundi, R. V., & Ardila, C. M. (2024). Integrating artificial intelligence into orthodontic education and practice. International Dental Journal, *74*(6), 1463. https://doi.org/10.1016/j.identj.2024.08.011
  37. Ye, X., Yan, Y., Li, J., & Jiang, B. (2024). Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective. Telecommunications Policy, *48*(10), 102851. https://doi.org/10.1016/j.telpol.2024.102851
  38. Yim, D., Khuntia, J., Parameswaran, V., & Meyers, A. (2024). Preliminary evidence of the use of generative AI in health care clinical services: Systematic narrative review. JMIR Medical Informatics, *12*, e52073. https://doi.org/10.2196/52073
  39. Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: Current status, issues, and prospects. Frontiers in Education, *8*, 1183162. https://doi.org/10.3389/feduc.2023.1183162
Scroll to Top