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

Authors

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

Published in

Surgical endoscopy. Jul 01, 2026. Epub Jul 01, 2026.

Abstract

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

PMID:
42387011
Bibliographic data and abstract were imported from PubMed on 02 Jul 2026.

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