@article{ajmsm20261412,
author={{Elbanna, Dr. Latifa and Karne, Dr. Soumya and Lopez, Dr. Dianela Zamora and Mansoor, Dr. Mahnoor and Daniel, Dr. Ajuwon Olumide and Movva, Dr. Sree Rekha and Singh, Dr. Sandeep},
title={The Digital Transformation of Dentistry: AI-Driven Innovations and Clinical Challenges},
journal={American Journal of Medical Sciences and Medicine},
volume={14},
number={1},
pages={7--12},
year={2026},
url={https://pubs.sciepub.com/ajmsm/14/1/2},
issn={2327-6657},
abstract={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.},
doi={10.12691/ajmsm-14-1-2}
publisher={Science and Education Publishing}
}