Artificial Intelligence in Prosthodontics: Current Applications, Clinical Readiness, Limitations and Future Directions

Abstract

Abstract Artificial intelligence (AI) is increasingly becoming integrated into digital dentistry and has the potential to transform prosthodontic diagnosis, treatment planning, prosthesis design, manufacturing and clinical decision-making. Machine learning and deep learning algorithms can analyze large volumes of radiographic, photographic, intraoral scanning and three-dimensional data and identify patterns that may be difficult to recognize consistently through conventional approaches. In prosthodontics, AI has been investigated for automated diagnosis, tooth and restoration identification, shade selection, preparation margin detection, crown design, removable partial denture planning, implant treatment planning and prediction of treatment outcomes. Recent systematic reviews indicate a substantial expansion of research in these areas, particularly in automated prosthesis design and implant-related applications. However, much of the available evidence remains based on retrospective, in vitro or highly controlled datasets, with considerable variation in data quality, algorithms, evaluation methods and reporting standards. Generative AI and large language models have further expanded the potential applications of AI into clinical documentation, education, patient communication and decision-support systems. Despite these advances, AI should currently be considered an adjunct to, rather than a replacement for, professional judgment. This review summarizes the current applications of AI in prosthodontics, evaluates the evidence supporting its clinical use, discusses limitations and ethical considerations, and outlines the transition from isolated AI tools toward integrated human–AI prosthodontic workflows.