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<p>This narrative review aims to evaluate the current landscape of Digital Smile Design (DSD) software platforms, with a focus on the integration of Artificial Intelligence (AI) to enhance clinical workflows. DSD is increasingly used in interdisciplinary dentistry to plan and simulate esthetic treatments, and AI has the potential to improve precision, efficiency, and patient engagement. The purpose was to analyze how AI-enabled DSD systems may influence treatment predictability, efficiency, and patient outcomes in digital dentistry. Literature was identified from PubMed Central, EBSCOhost, Scopus, and Web of Science over the past 15&#xa0;years, focusing on peer-reviewed studies describing the progression of DSD from basic 2D visualization tools to advanced AI-assisted 3D platforms. A total of 12 software platforms and 6 peer-reviewed studies reporting AI integration in DSD were analyzed. The review highlights how such systems enable more precise smile simulations, semi-automated treatment planning, and interdisciplinary collaboration across orthodontics, prosthodontics, and implantology. Reported outcomes indicate reduced design time, improved interdisciplinary communication, and enhanced patient engagement. However, the limited number and heterogeneity of available studies constrain definitive conclusions. Thus, AI integration shows potential benefits, but further controlled studies are required before definitive clinical recommendations can be made. This review identifies current applications, limitations, and future research needs for integrating AI technologies into patient-centered digital dentistry. </p>

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Artificial intelligence in digital smile design: a review of technological innovations and clinical integration

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月9日

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  • Ashish Kumar Singh,
  • Dhruv Ahuja,
  • Susmita Mallick,
  • Nidhin Philip Jose,
  • Isha Bhardwaj,
  • Puneet Batra,
  • Anju Rana

摘要

This narrative review aims to evaluate the current landscape of Digital Smile Design (DSD) software platforms, with a focus on the integration of Artificial Intelligence (AI) to enhance clinical workflows. DSD is increasingly used in interdisciplinary dentistry to plan and simulate esthetic treatments, and AI has the potential to improve precision, efficiency, and patient engagement. The purpose was to analyze how AI-enabled DSD systems may influence treatment predictability, efficiency, and patient outcomes in digital dentistry. Literature was identified from PubMed Central, EBSCOhost, Scopus, and Web of Science over the past 15 years, focusing on peer-reviewed studies describing the progression of DSD from basic 2D visualization tools to advanced AI-assisted 3D platforms. A total of 12 software platforms and 6 peer-reviewed studies reporting AI integration in DSD were analyzed. The review highlights how such systems enable more precise smile simulations, semi-automated treatment planning, and interdisciplinary collaboration across orthodontics, prosthodontics, and implantology. Reported outcomes indicate reduced design time, improved interdisciplinary communication, and enhanced patient engagement. However, the limited number and heterogeneity of available studies constrain definitive conclusions. Thus, AI integration shows potential benefits, but further controlled studies are required before definitive clinical recommendations can be made. This review identifies current applications, limitations, and future research needs for integrating AI technologies into patient-centered digital dentistry.