| Despite the great potential of artificial intelligence (AI) in healthcare, many applications remain unused in practice due to numerous challenges. Beyond legal and ethical issues, the integration of AI faces technical, economic, and user-related barriers that must be overcome. This work aims to identify key factors and practical implications for successful AI adoption and evaluates the potential of human-in-the-loop (HITL) systems. Therefore a qualitative approach based on semi-structured expert interviews is used. Key factors identified include perceived user benefits, ease of use, integration into existing workflows, the availability of technical infrastructure and high-quality data. Additionally, expert recommendations emphasized the importance of training for medical stakeholders to support effective use. HITL was considered as a promising approach to enhance the adoption of AI in healthcare. Further, this study suggest that HITL systems play a central role in the continuous improvement of AI applications by providing a feedback loop for adaptation to regional contexts, specific use-cases, and institutions. The study contributes to a deeper understanding of how AI can be adapted to the specific demands of the healthcare sector and generate tangible benefits in practice. |
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