Perception and Application of Dental Artificial Intelligence in Orthodontic Clinical Practice: A Cross-Sectional Survey of Orthodontists in Iraq

Noor Nadheer Al-Taie; Shaho Ziyad Al-Talabani

doi:10.54133/ajms.v9i1.2050

Authors

Noor Nadheer Al-Taie Department of Orthodontics, College of Dentistry, Hawler Medical University, Erbil, Kurdistan Region, Iraq https://orcid.org/0009-0005-2261-1771
Shaho Ziyad Al-Talabani Department of Orthodontics, College of Dentistry, Hawler Medical University, Erbil, Kurdistan Region, Iraq https://orcid.org/0000-0002-1343-3310

DOI:

https://doi.org/10.54133/ajms.v9i1.2050

Keywords:

Artificial intelligence, Attitudes of health personnel, Clinical practice, Knowledge, Orthodontics, Perceptions

Abstract

Background: The adoption of artificial intelligence is rapidly expanding and has significantly influenced orthodontic practice. Objective: To investigate specialized orthodontists' perceptions and attitudes toward artificial intelligence in orthodontic practice. Methods: An anonymous, web-based cross-sectional survey was conducted using Google Forms. An expert panel evaluated the survey instrument for content validity using Lawshe's method and for face validity by measuring inter-rater reliability. The survey comprised 25 closed-ended and one open-ended question organized into six sections. After its official release, the survey link was disseminated to all Iraqi Orthodontic Society members from January to March 2025. Descriptive statistics were performed to categorize the age groups of the participants. Results: 101 valid surveys were collected and analyzed, highlighting a 63% response rate. The results revealed that although most respondents (61.4%) were aware of using AI-driven software programs, a significant percentage (40.6%) reported that they had never used such programs, underscoring a certain level of deficiency in applying AI in orthodontic practice. The awareness level was higher for AI applications in cephalometric analysis (60.0%) compared to other applications, such as orthognathic surgery and the biomechanics domain. Conclusions: Generally, there was a good level of awareness and knowledge about AI's role in orthodontics, with strong readiness among the specialists to engage in AI-related training and integrate it into their clinical routines. The study supports further education, training, evidence-based validation, and designing more AI-powered tools addressing different domains of orthodontics, particularly biomechanics, which are essential to bridge the trust gap.

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