The article discusses the implementation of cloud computing in the German healthcare system, emphasizing the need for digitization in response to technological advancements and the challenges of integrating cloud solutions while maintaining data privacy. It outlines the role of European data protection laws, particularly the GDPR, in shaping the integration of cloud computing in healthcare. The authors present a model approach used at Charité – University Hospital Berlin, which demonstrates how cloud computing can be implemented within existing hospital information systems (HIS) without full integration. This model emphasizes interoperability, data security, and the use of standards like HL7v2 and FHIR to ensure seamless data exchange. Cloud computing is described as a flexible and scalable solution that enables the sharing of medical data, supports clinical research, and improves patient care through data-driven insights. The article highlights the importance of data protection, especially in handling sensitive patient information, and discusses the legal requirements for cloud computing in Germany and the EU, including the GDPR and national laws such as the BDSG and LKHG. It also addresses the challenges of ensuring data privacy and security in cloud-based systems, including the need for encryption, anonymization, and strict access controls. The article also explores the integration of AIQNET, a consortium focused on developing cloud-based solutions for medical AI applications. It describes the technical and legal framework for implementing cloud computing in healthcare, including the use of standardized data models and APIs to ensure interoperability. The AIQNET project aims to create a secure and efficient ecosystem for data sharing, research, and clinical decision-making, while complying with legal and ethical standards. The article concludes that cloud computing has the potential to revolutionize healthcare by enabling better data integration, improving patient outcomes, and supporting evidence-based medicine, provided that data privacy and security are carefully managed.The article discusses the implementation of cloud computing in the German healthcare system, emphasizing the need for digitization in response to technological advancements and the challenges of integrating cloud solutions while maintaining data privacy. It outlines the role of European data protection laws, particularly the GDPR, in shaping the integration of cloud computing in healthcare. The authors present a model approach used at Charité – University Hospital Berlin, which demonstrates how cloud computing can be implemented within existing hospital information systems (HIS) without full integration. This model emphasizes interoperability, data security, and the use of standards like HL7v2 and FHIR to ensure seamless data exchange. Cloud computing is described as a flexible and scalable solution that enables the sharing of medical data, supports clinical research, and improves patient care through data-driven insights. The article highlights the importance of data protection, especially in handling sensitive patient information, and discusses the legal requirements for cloud computing in Germany and the EU, including the GDPR and national laws such as the BDSG and LKHG. It also addresses the challenges of ensuring data privacy and security in cloud-based systems, including the need for encryption, anonymization, and strict access controls. The article also explores the integration of AIQNET, a consortium focused on developing cloud-based solutions for medical AI applications. It describes the technical and legal framework for implementing cloud computing in healthcare, including the use of standardized data models and APIs to ensure interoperability. The AIQNET project aims to create a secure and efficient ecosystem for data sharing, research, and clinical decision-making, while complying with legal and ethical standards. The article concludes that cloud computing has the potential to revolutionize healthcare by enabling better data integration, improving patient outcomes, and supporting evidence-based medicine, provided that data privacy and security are carefully managed.