Background/Objectives: This scoping review aims to map existing AI applications in dental education, in student learning, assessment, and diagnostic training, identifying key limitations and challenges. Methods: Following the Arksey and O’Malley framework and PRISMA-ScR guidelines, six databases were searched in March 2025 using combinations of the following search words: “dental education,” “artificial intelligence,” “machine learning,” and “student assessment”. Inclusion was limited to English-language empirical studies focused on dental student education. Of 547 identified studies, 17 met the inclusion criteria. They were categorized into four domains: (1) Preclinical Training, (2) AI in Clinical, Diagnostic Training, and Radiographic Interpretation, (3) AI as an Assessment Tool and Feedback System, and (4) AI in Content Generation for Dental Education. Results: AI has positively influenced various domains, enhancing procedural accuracy, diagnostic confidence, assessment efficiency, and content delivery. However, it struggles to assess nuanced competencies like dexterity and clinical judgment. The challenges faced include disparate definitions of AI, ethical and privacy concerns, model variability, and a deficiency of dental leadership in AI development. At present, most tools are engineered by computer scientists and may not align effectively with the priorities of dental education. Conclusions: AI holds significant potential to enhance dental education outcomes. However, to guarantee its relevance and reliability, it requires standard frameworks, ethical oversight, and clinician-led development. Future research should concentrate on implementing real-time AI-driven feedback systems during preclinical training and advocate for more precise definitions to support consistent AI application and evaluation in dental education.

To study the antimicrobial effects of quaternary ammonium silane (QAS) exposure on Streptococcus mutans and Lactobacillus acidophilus bacterial biofilms at different concentrations. Streptococcus mutans and Lactobacillus acidophilus biofilms were cultured on dentine disks, and incubated for bacterial adhesion for 3-days. Disks were treated with disinfectant (experimental QAS or control) and returned to culture for four days. Small-molecule drug discovery-suite was used to analyze QAS/Sortase-A active site. Cleavage of a synthetic fluorescent peptide substrate, was used to analyze inhibition of Sortase-A. Raman spectroscopy was performed and biofilms stained for confocal laser scanning microscopy (CLSM). Dentine disks that contained treated dual-species biofilms were examined using scanning electron microscopy (SEM). Analysis of DAPI within biofilms was performed using CLSM. Fatty acids in bacterial membranes were assessed with succinic-dehydrogenase assay along with time-kill assay. Sortase-A protein underwent conformational change due to QAS molecule during simulation, showing fluctuating alpha and beta strands. Spectroscopy revealed low carbohydrate intensities in 1% and 2% QAS. SEM images demonstrated absence of bacterial colonies after treatment. DAPI staining decreased with 1% QAS (p < 0.05). Fatty acid compositions of dual specie biofilm increased in both 1% and 2% QAS specimens (p < 0.05). Quaternary ammonium silane demonstrated to be a potent antibacterial cavity disinfectant and a plaque inhibitor and can be of potential significance in eliminating caries-forming bacteria.