Abstract Organisations are increasingly adopting multiple cloud platforms to optimize costs, reduce vendorlock-in, and leverage platform-specific capabilities. Nonetheless, cross-platform cloud databaseinteroperability remains a challenge as a result of differences in data formats, security policies, andperformance optimization needs. This study examines the role of Artificial Intelligence (AI) inenabling seamless data migration and integration across multi-cloud environments. The adoptionof AI-driven solutions boosts interoperability by automating data migration, optimizing data flowperformance, and mitigating potential risks through predictive analytics. While AI-driveninteroperability solutions offer significant advantages, they face some challenges such as the needfor high-quality training data that are difficult to obtain, the performance trade-offs between speedand accuracy, and ensuring regulatory compliance. Overcoming these challenges requirescontinuous development of the AI model and investing in scalable computing infrastructure whilealso not overlooking security measures to avoid data losses. This study highlights thetransformative potential of AI in multi-cloud database interoperability