Digitale Transformation und künstliche Intelligenz in der Radiologie: Herausforderungen und Chancen für Klinik, Forschung und Nachwuchs

Background: Radiology is at the center of the digital transformation of the healthcare system. As a highly digital field, radiology is well-suited for the early implementation and critical evaluation of innovative technologies, such as artificial intelligence (AI). This review aims to comprehensively and distinctly present the opportunities and challenges of digital transformation in radiology, focusing on clinical applications, research, and promoting young talents. Materials and Methods: This narrative review is based on selective evaluation of relevant scientific literature and publications from the last 10 years. Relevant German- and English-language articles on the digital transformation of radiology were considered, particularly those addressing digital infrastructure, artificial intelligence, ethical and regulatory frameworks, and education and training. Results and Conclusion: Digitalization offers significant opportunities for radiology. In addition to advancing imaging procedures and automating image analysis with AI, digitalization optimizes workflows, enables personalized diagnostics, and fosters new care models, such as teleradiology. However, there are also key challenges: Data protection issues, a lack of standardization, insufficient validation, and regulatory hurdles are hindering its widespread implementation in hospitals. To future-proof radiology, it is essential to promote young talent and incorporate digital skills in the curriculum. Key Points: · Due to its digital structure, radiology is particularly well-suited to integrating new medical technologies.. · Some AI-powered applications have been adopted in everyday clinical practice but they require further validation.. · A key task for the future is systematically training prospective radiologists in digital skills.. Citation Format: · Hoffmann E, Bannas P, Bayerl N et al. Digital Transformation and Artificial Intelligence in Radiology: Challenges and Opportunities for Clinical Practice, Research, and the Next Generation. Rofo 2025; DOI 10.1055/a-2741-9717.