Liquid artificial intelligence is a dynamic data processing approach that enables real-time, adaptable management and analysis of data across various platforms. So far, Liquid AI has been considered as a technical concept, and there are no studies that relate it to data governance frameworks such as those proposed by the international data spaces association and GAIA-X, which play a key role when setting standards for data sovereignty, security, and interoperability. To address this gap, we propose a reference architecture and algorithms for integrating the IDSA and GAIA-X frameworks within the context of Liquid AI, with a focus on their application in Intelligent Hospital Management and Intelligent Traffic Control systems. Based on the study, future work will focus on experimentally and empirically evaluating the proposed reference architecture in real-world settings and exploring its interoperability with other frameworks, as well as integrating emerging technologies to improve its effectiveness.