Mapping the Influence of Artificial Intelligence in Prosthodontics: A Scoping Review of the Current Trends and Challenges.

Background/

Objectives

Artificial intelligence (AI) is transforming prosthodontic procedures into data-driven support systems. This scoping review systematically maps the literature using an evidence maturity framework, distinguishing it from recent applications-focused compilations by Aljulayfi, Schwendicke, and others.

Methods

A comprehensive search of PubMed, Scopus, and Web of Science (January 2023-March 2026) was conducted in accordance with PRISMA-ScR guidelines, supplemented by targeted manual citation tracking. Fifty studies were included in the review.

Results

The evidence base comprises approximately half primary research (computational, in vitro, clinical) and half review articles. Foundational diagnostic CNNs report high technical performance metrics (i.e., sensitivity 98.67%, precision 78.12%), while generative CAD/CAM approaches reduce design time by up to 52% in vitro. However, the evidence synthesis reveals a significant gap between algorithmic efficacy and clinical utility. Most applications currently reside at the "technical validation" stage, while emerging domains such as large language models remain largely experimental.

Conclusions

Impressive computational metrics do not automatically equate to patient-centered clinical benefits. Current AI systems must be regarded as adjunctive decision-support instruments rather than autonomous tools. Future research must prioritize prospective multicenter validation, implementation science, explainability, and robust regulatory oversight.