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European Journal of Prosthodontics and Restorative Dentistry  —  Vol. 34, Issue Special Issue 5 (July 2026) ← Back to issue
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Workflow Intelligence: An Examination of AI-Powered Prosthodontic Diagnostics and Design A Review of literatures

DOI: 10.1922/ejprd.v34i5s.1549
Keywords

Artificial Intelligence, Digital dentistry, fixed prosthodontics, Digital smile design

Authors

Zhiyar Ameen Ali*
*Ministry of health, Xanzad teaching center,
Prosthodontic department.
jiyar1987315@gmail.com
https://orcid.org/0000-0002-3398-2253

Ranj Azad Omer **
** Knowledge University, Department of
Dental technology. ranj.omer@knu.edu.iq
https://orcid.org/0009-0004-8106-7887

Received: 18-06-2026
Revised: 20-07-2026
Accepted: 24-07-2026

European Journal of Prosthodontics and Restorative Dentistry (2026) 34(5S), 223-231

Workflow Intelligence: An Examination of AI-Powered Prosthodontic Diagnostics and Design A Review of literatures

Abstract

With a focus on digital workflows, diagnostic assistance, and computer-aided design and manufacturing procedures, this narrative review examines current uses of artificial intelligence (AI) in prosthodontics. Relevant peer-reviewed research on clinically usable AI-driven techniques in fixed and removable prosthodontics that has been published recently was found in large scientific databases. An analysis of multiple peer-reviewed publications revealed that AI plays a significant role in the interpretation in prosthodontics (e.g., impressions, implant placement, and 3D designing) to support diagnosis and treatment planning. Clinically speaking, the evidence currently available supports the use of AI mainly as a decision-support tool in digital prosthodontic workflows, especially in margin detection and prosthetic design. However, routine clinical adoption of AI is still constrained by inadequate validation and practical applicability. Clinically speaking, the evidence currently available supports the use of AI mainly as a decision-support tool in digital prosthodontic workflows, particularly in margin detection and prosthetic design. However, routine clinical implementation of AI is still inhibited by inadequate validation and practical applicability. Aim of the Study The aim of this study is to systematically evaluate the assimilation of AI technologies in modern dentistry, quantifying their sway on diagnostic accuracy, treatment planning workflows, and clinic operational efficiency.

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Article Information
Pages
223 – 231
Cover Date
July 2026
Volume
34
Issue
Special Issue 5
Print ISSN
0965-7452
Electronic ISSN
2396-8893