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Background <p>The integration of artificial intelligence (AI) and large language models (LLMs) into surgical practice is increasingly being explored, but real-world usage patterns and barriers remain insufficiently characterized. This multinational survey assessed self-reported AI/LLM use, perceived benefits, and requirements for routine implementation among general surgeons in German-speaking countries.</p> Methods <p>Between June and September 2025, a 16-item online survey was conducted among general surgeons at university hospitals in Germany, Austria, and Switzerland.</p> Results <p>Of 3831 invited surgeons, 323 complete responses were analyzed (response rate 8.7%). Self-reported AI use was frequent: 58.5% reported occasional and 28.2% regular use. The most frequent applications were speech recognition (65.3%) and chatbots (62.8%). Anticipated benefits focused on documentation simplification (94.4%), reduced administrative time (84.2%) as well as burden (83.0%), and improved diagnostic accuracy (70.6%). ChatGPT was the leading chatbot (89.8%), chatbot use was rated helpful (69.6%), and the most common use case was scientific writing (51.4%). Key barriers to routine AI adoption were insufficient integration into existing systems (77.1%), legal/data-protection uncertainty (65.9%), and lack of validated applications (59.1%). The most important requirements were system reliability (76.2%), a clear legal framework (72.1%), improved technical infrastructure (68.4%), and transparency (58.5%). Most respondents expected AI to improve surgical care quality (82.4%) and endorsed structured AI training (85.1%).</p> Conclusion <p>The use of AI and LLM-based chatbots was commonly reported among general surgeons in German-speaking countries, primarily for low-threshold, efficiency-oriented tasks such as speech recognition, documentation, scientific writing, and other text-based productivity. Broader integration into surgical workflow will require interoperable implementation, validated clinical-grade applications, legal clarity, and structured education.</p>

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Artificial intelligence and chatbots in general surgery: a survey among surgeons in Germany, Austria and Switzerland

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月1日

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  • Sebastian Lünse,
  • Eric L. Wisotzky,
  • Lasse Renz-Kiefel,
  • Christoph Paasch,
  • Richard Hunger,
  • René Mantke

摘要

Background

The integration of artificial intelligence (AI) and large language models (LLMs) into surgical practice is increasingly being explored, but real-world usage patterns and barriers remain insufficiently characterized. This multinational survey assessed self-reported AI/LLM use, perceived benefits, and requirements for routine implementation among general surgeons in German-speaking countries.

Methods

Between June and September 2025, a 16-item online survey was conducted among general surgeons at university hospitals in Germany, Austria, and Switzerland.

Results

Of 3831 invited surgeons, 323 complete responses were analyzed (response rate 8.7%). Self-reported AI use was frequent: 58.5% reported occasional and 28.2% regular use. The most frequent applications were speech recognition (65.3%) and chatbots (62.8%). Anticipated benefits focused on documentation simplification (94.4%), reduced administrative time (84.2%) as well as burden (83.0%), and improved diagnostic accuracy (70.6%). ChatGPT was the leading chatbot (89.8%), chatbot use was rated helpful (69.6%), and the most common use case was scientific writing (51.4%). Key barriers to routine AI adoption were insufficient integration into existing systems (77.1%), legal/data-protection uncertainty (65.9%), and lack of validated applications (59.1%). The most important requirements were system reliability (76.2%), a clear legal framework (72.1%), improved technical infrastructure (68.4%), and transparency (58.5%). Most respondents expected AI to improve surgical care quality (82.4%) and endorsed structured AI training (85.1%).

Conclusion

The use of AI and LLM-based chatbots was commonly reported among general surgeons in German-speaking countries, primarily for low-threshold, efficiency-oriented tasks such as speech recognition, documentation, scientific writing, and other text-based productivity. Broader integration into surgical workflow will require interoperable implementation, validated clinical-grade applications, legal clarity, and structured education.