Clinical and Patient Comparison of AI and Expert Digital Smile Design: A Prospective Paired Study

<b>Background</b>: Artificial intelligence (AI) systems are increasingly being used in digital smile design and esthetic treatment planning; however, evidence comparing the esthetic performance of AI-generated designs with expert clinician-generated designs remains limited. Objective evaluation using standardized esthetic indices is necessary to determine whether AI-generated outcomes achieve comparable clinical quality. <b>Methods</b>: This prospective paired comparative study included 33 patients. For each case, two smile designs were created: one generated using a fully automated AI system (SmileFy) and one designed manually by an experienced clinician using Exocad software(version 3.2 Elefsina; exocad GmbH, Darmstadt, Germany). Twenty blinded prosthodontists evaluated all designs using the Dental Esthetic Screening Index (DESI) and a visual analog scale (VAS). Patients provided esthetic VAS ratings and forced-choice preferences. Objective geometric measurements and total design time were recorded. Paired statistical analyses were performed with a significance level of <i>p</i> < 0.05. <b>Results</b>: AI-generated designs demonstrated significantly lower total DESI scores than expert-generated designs (14.79 ± 1.63 vs. 18.73 ± 1.82; <i>p</i> < 0.001). Both expert and patient VAS ratings were significantly higher for AI designs (<i>p</i> < 0.001). Patients preferred AI-generated designs in 69.7% of cases compared with 30.3% for expert designs (<i>p</i> < 0.001). AI workflows were significantly faster, with a mean design time of 30.82 ± 5.14 min versus 63.48 ± 14.12 min for expert workflows, corresponding to a 51.46% reduction in planning time (<i>p</i> < 0.001). <b>Conclusions</b>: Fully automated AI-generated smile designs demonstrated favorable esthetic performance, higher patient acceptance, and substantial improvements in workflow efficiency compared with expert-driven digital designs, supporting their potential role as adjunctive tools in esthetic treatment planning.