Related Experiment Video
Updated: May 6, 2026
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Artificial Intelligence (AI) Impact on Dental Education and Curriculum: A Systematic Review Following PRISMA
Laura Reyes Alardo1,2, Franklin García-Godoy3, Romina Paola Quiroga4
1Universidad Federico Henríquez y Carvajal (UFHEC), Santo Domingo, Dominican Republic.
Importance:
AI technologies increasingly influence dental education, but their instructional value, stakeholder perspectives, and institutional implications require further study.
Objective:
To synthesise evidence on AI's impact in undergraduate dental education, focusing on learning outcomes, stakeholder perspectives, and curriculum design.
Evidence Review:
Following PRISMA 2020 guidelines, researchers searched PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar for articles published between January 2015 and February 2025. Eligibility followed an adapted PECO framework: undergraduate dental students or faculty (Population); AI use in teaching, clinical training, or administration (Exposure); conventional or non-AI digital methods (Comparator); and outcomes including knowledge retention, skills, critical thinking, stakeholder perspectives, and curriculum effectiveness (Outcome). The initial pool of 402 references underwent systematic screening, quality appraisal, and AI-focused refinement across four stages, resulting in a final dataset of 107 studies meeting a minimum quality threshold (≥ 3) using validated appraisal tools.
Findings:
AI-powered educational resources, including adaptive learning platforms, intelligent tutoring systems, and generative AI tools, improved knowledge retention, technical skills, and clinical decision-making. Students benefited from personalised feedback, adaptive instruction, and increased engagement. Faculty expressed cautious optimism, tempered by gaps in training, technical readiness, and ethical guidance. Adoption patterns were shaped by generational, cultural, and infrastructural factors.
Conclusions:
AI enhances cognitive, technical, and clinical learning while complementing traditional instruction. Successful integration requires structured faculty development, clear ethical frameworks, institutional support, and close collaboration among educators, researchers, and technologists to ensure AI supports, rather than replaces, core clinical training and professional decision-making. Coordinated strategies addressing pedagogy, technical competence, and ethics will maximise AI's educational impact and support sustainable curriculum transformation in dental education.