eng Science and Education Publishing American Journal of Medical Sciences and Medicine 2327-6657 2026-03-30 14 1 7 12 10.12691/ajmsm-14-1-2 AJMSM20261412 article Dr. Latifa Elbanna 1 Dr. Soumya Karne Dr.soumyakarne04@gmail.com 2 Dr. Dianela Zamora Lopez 3 Dr. Mahnoor Mansoor 4 Dr. Ajuwon Olumide Daniel 5 Dr. Sree Rekha Movva 6 Dr. Sandeep Singh 7 (PhD, Prosthodontics) Faculty of Dental Medicine - AlAzhar University, Cairo, Egypt BDS, Government Dental College and Hospital, Vijayawada, Andhra Pradesh, India Doctor in Stomatology, University of Medical Sciences of Cienfuegos, Cienfuegos, Cuba BDS, Riphah International university, Islamabad, Pakistan College of Medicine, University of Ibadan, Ibadan, Nigeria BDS, Kamineni Institute of Dental Sciences. Sreepuram, Akkinepallivari Lingotam, Telangana, India MDS (Prosthodontics), Post Graduate Institute of Dental Sciences, Rohtak, India Artificial intelligence (AI) and digital technologies are increasingly reshaping contemporary dental practice, influencing diagnostic accuracy, treatment planning, and clinical workflows across multiple dental specialties. This review synthesizes current evidence on the clinical applications of AI and digital dentistry, with particular emphasis on diagnostic imaging, intraoral scanning, CAD/CAM systems, three-dimensional (3D) printing, and integrated digital workflows in prosthodontics, orthodontics, implantology, and surgical dentistry. AI-assisted diagnostic systems demonstrate promising performance in radiographic interpretation, occlusal analysis, and early lesion detection, supporting clinical decision-making and reducing diagnostic variability. Digital technologies, including intraoral scanning and additive manufacturing, enhance treatment precision, chairside efficiency, patient comfort, and communication while facilitating streamlined documentation and interdisciplinary collaboration. However, challenges related to high initial investment costs, clinician training, data privacy, cybersecurity, and the need for robust clinical validation of AI algorithms continue to limit widespread adoption. Evidence from current literature indicates that while these technologies offer substantial benefits as adjuncts to clinical expertise, their successful integration into routine dental practice requires evidence-based implementation, standardized clinical protocols, and continued validation through high-quality clinical and outcome-based research. https://pubs.sciepub.com/ajmsm/14/1/2/ajmsm-14-1-2.pdf Artificial intelligence Digital dentistry Intraoral scanning CAD/CAM 3D printing Dental diagnostics Clinical workflows Prosthodontics Orthodontics Implant dentistry