International Journal of Chemical and Biochemical Sciences (ISSN 2226-9614)[/vc_column_text][/vc_column][/vc_row]
VOLUME 29(23) (2026)
Accuracy of Restorations Designed by Artificial Intelligence and Conventional Software: A Narrative Review
Rana Hatem Hanafy Mahmoud1*, Maged Mohammed Zohdy2, Hoda Mohamed Abdel Sadek3, Fatma Adel Mohamed Ahmed4, Tarek Mohamed ElSaaedi5
1*,2,3,4Fixed Prosthodontics Department, Faculty of Dentistry, Ain Shams University, Cairo, Egypt.
5Oral and Maxillofacial Prosthodontics Department, Faculty of Dentistry, Ain Shams University, Cairo, Egypt.
Abstract
Advancements in computer aided designing/computer aided manufacturing (CAD/CAM) technology have enhanced the precision and efficiency of indirect restorations; however, conventional workflows remain operator-dependent and require technical expertise for accurate customization. Recently, artificial intelligence (AI)–based design platforms have emerged to automate crown generation, aiming to reduce technique sensitivity and improve workflow consistency. Nevertheless, evidence regarding the accuracy and reliability of these systems remains limited. The success of CAD/CAM restorations is influenced by multiple variables, including preparation design, scanning accuracy, CAD algorithms, manufacturing processes, and material properties, with errors at any stage potentially compromising restorative accuracy. The aim of this narrative review was to synthesize current evidence comparing conventional and AI-driven CAD software, with emphasis on internal fit, marginal adaptation, restoration morphology, and the reliability of finish line detection. Available data suggests that AI-based systems can achieve accuracy comparable to conventional workflows, supporting their potential clinical feasibility, although further validation studies are warranted.
Keywords: CAD/CAM, Artificial intelligence, Accuracy, CAD software, Digital dentistry
Full length article *Corresponding Author, e-mail: rana.mahmoud.std1@dent.asu.edu.eg, Doi # https://doi.org/10.62877/6-IJCBS-26-29-23-6
Submitted: 04-03-2026; Accepted: 09-04-2026; Published: 11-04-2026