International Journal of Chemical and Biochemical Sciences (ISSN 2226-9614)[/vc_column_text][/vc_column][/vc_row]
VOLUME 29(23) (2026)
Artificial Intelligence-Assisted and Conventional CAD Software for Smile Design: A Critical Review
Mariam Ahmed Dorgham*, Mohamed Adel ElDemellawy, Maged Mohammed Zohdy, Marwa Mahmoud Emam
Fixed Prosthodontics Department, Faculty of Dentistry, Ain Shams University, Organization of African Unity St, El-Qobba Bridge, El Weili, Cairo, Egypt
Abstract
The evolution of digital smile design (DSD) has transitioned from manual 2D drawings to sophisticated 3D workflows, with artificial intelligence (AI) emerging as a transformative tool in prosthodontics. While conventional CAD software remains the gold standard for clinical precision, AI integration promises to automate complex tasks like facial analysis and prosthetic simulation. This narrative review evaluates the impact of AI-integrated platforms compared to conventional CAD software in DSD, focusing on workflow efficiency, clinical precision, and aesthetic outcomes. Comparative literature reveals a significant discrepancy. AI-driven workflows offer superior efficiency, reducing average planning time from 63.48 minutes to 30.82 minutes. However, aesthetic evaluations remain inconsistent; while patients often accept AI-generated designs, expert prosthodontists maintain a preference for the artistic characterization and secondary anatomy provided by manual CAD systems. Current evidence indicates that while AI is an essential, high-efficiency adjunct that streamlines planning, it does not replace the artistic intuition and oversight of the prosthodontist. Future practice should adopt a hybrid approach, leveraging AI’s computational speed for initial simulations while maintaining strict manual control over definitive design parameters to ensure individualized patient care.
Keywords: Digital Smile Design (DSD), Artificial Intelligence, Digital Dentistry, CAD Software.
Full length article *Corresponding Author, e-mail: mariam.dergham.std@dent.asu.edu.eg; Doi # https://doi.org/10.62877/23-IJCBS-26-29-23-23
Submitted: 05-06-2026; Accepted: 06-07-2026; Published: 07-07-2026
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