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Background <p>The integration of artificial intelligence (AI) into urological robotic surgery is currently in a&#xa0;dynamic phase of development and validation. Minimally invasive, standardized, and video-based procedures create highly data-rich operative environments with clearly defined workflow steps, thereby providing ideal conditions for the development of AI-based systems.</p> Objective <p>The objective of this work is to present the current state of AI integration in urological robotic surgery, to classify existing clinically available applications, and to critically evaluate the perspective of autonomous systems. Technological, regulatory, and clinical aspects are considered in equal measure.</p> Materials and methods <p>An analysis of the current literature was conducted, along with a&#xa0;systematic review of clinically available robotic platforms and experimental systems. Both approved medical devices with integrated AI functionalities and preclinical developments in the field of semi-autonomous and autonomous surgical modules were included. In addition, international research initiatives aimed at advancing autonomous surgical systems were taken into account.</p> Conclusion <p>Current developments primarily focus on supportive systems such as environment modeling and augmented reality (AR) navigation. Clinically approved platforms increasingly benefit from data-driven performance analytics, optimized treatment planning, and enhanced teleoperative structures. As the level of autonomy increases, the requirements for validation, regulation, and liability frameworks also become more demanding. Urological robotic surgery is therefore undergoing a&#xa0;paradigm shift—from purely teleoperated assistance toward adaptive, semi-autonomous systems. This transition is driven not only by technological innovation but also by international research and investment programs, and it necessitates structural adaptations in surgical training, quality control, and legal frameworks.</p>

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Künstliche Intelligenz in der Urochirurgie

  • 期刊论文

  • 发表日期：

    2026年5月21日

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  • Sami-Ramzi Leyh-Bannurah,
  • Felix Chun,
  • Hendrik Borgmann,
  • Christian Wülfing,
  • Radu Alexa

摘要

Background

The integration of artificial intelligence (AI) into urological robotic surgery is currently in a dynamic phase of development and validation. Minimally invasive, standardized, and video-based procedures create highly data-rich operative environments with clearly defined workflow steps, thereby providing ideal conditions for the development of AI-based systems.

Objective

The objective of this work is to present the current state of AI integration in urological robotic surgery, to classify existing clinically available applications, and to critically evaluate the perspective of autonomous systems. Technological, regulatory, and clinical aspects are considered in equal measure.

Materials and methods

An analysis of the current literature was conducted, along with a systematic review of clinically available robotic platforms and experimental systems. Both approved medical devices with integrated AI functionalities and preclinical developments in the field of semi-autonomous and autonomous surgical modules were included. In addition, international research initiatives aimed at advancing autonomous surgical systems were taken into account.

Conclusion

Current developments primarily focus on supportive systems such as environment modeling and augmented reality (AR) navigation. Clinically approved platforms increasingly benefit from data-driven performance analytics, optimized treatment planning, and enhanced teleoperative structures. As the level of autonomy increases, the requirements for validation, regulation, and liability frameworks also become more demanding. Urological robotic surgery is therefore undergoing a paradigm shift—from purely teleoperated assistance toward adaptive, semi-autonomous systems. This transition is driven not only by technological innovation but also by international research and investment programs, and it necessitates structural adaptations in surgical training, quality control, and legal frameworks.