Artificial intelligence and the future of prosthodontics: a narrative review

This narrative review aims to systematically summarize and compile available evidence on the applications of artificial intelligence (AI) across major domains of prosthodontics, including complete dentures, removable partial dentures, fixed prosthodontics, implant-supported prosthodontics, and maxillofacial prosthetics.

A structured search of the literature was carried out using the PubMed and Scopus databases, along with manual screening of relevant journals, to identify peer-reviewed clinical, experimental, and review studies published between 2006 and 2025. Search strategies incorporated combinations of keywords related to "artificial intelligence", "machine learning", "deep learning", and "neural network" as well as prosthodontic domain-specific terms. A total of 54 studies that met the inclusion criteria were selected for analysis. Because of variability in study designs, datasets, and reported outcomes, a quantitative meta-analysis was not feasible, so findings were synthesized using a descriptive narrative approach. This review was conducted as a narrative study and did not adhere to a PRISMA protocol.

The included studies show that artificial intelligence applications in prosthodontics are predominantly concentrated in implant prosthodontics, followed by fixed and removable prosthodontics. AI methodologies were frequently applied to arch classification, image interpretation, predictive modeling, prosthesis design, implant system recognition, and workflow optimization, with many studies reporting accuracy levels exceeding 90% under controlled conditions. Despite these results, most evidence is derived from retrospective or experimental settings, with limited prospective clinical validation. Commonly reported challenges include data quality, lack of model transparency, ethical considerations, and difficulties in the use of AI systems in routine clinical workflows.

Current evidence indicates that artificial intelligence has been widely explored as a supportive adjunct within digital prosthodontic workflows. Further standardized validation, prospective clinical studies, and ethical oversight are required to clarify clinical applicability and guide responsible integration into routine prosthodontic practice.