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Through changes in the digital world, organisations are moving towards multi-cloud strategy, which includes platforms like AWS, Microsoft Azure, and Google cloud, to become more agile, cost-efficient and to escape the problem of vendor lock options. Nevertheless, this change has introduced severe challenges in terms of business data security because of its complexity, unique setup, as well as expansion of its attack surface. This paper examines the technical and the strategic challenges involved in protecting business data in a multi-cloud setting through assessment of threats, and integration challenges, and the use of advanced security models. They focus on AI-based threat detection, zero-trust structures, and cloud-native application protection platforms (CNAPPs) and the role they play in reinforcing data security. This study takes an interpretivist philosophy, qualitative approach, and secondary sources to a thematic analysis to evaluate existing tools, frameworks, and limitations. It also goes into dynamic threat categories and the need to have common governance over cloud environments. The evidence requires the level of continuous identity and access management (IAM), monitoring on a real-time basis, and safe API integration. While technological advancements offer robust security solutions, the study notes challenges in implementation, cost, and scalability. The analysis supports a holistic security approach combining automation, standardisation, and strategic policy enforcement. This ensures operational resilience, compliance, and trust in managing business data across complex multi-cloud ecosystems.