Building Trust in the Future of Cloud Computing in a Data-Driven and AI-Powered World

The convergence of cloud computing, big data, and artificial intelligence (AI) is changing industries and making them scalable and innovative faster than ever before. Nevertheless, this integration also brings forth deep issues of building and sustaining trust among the stakeholders. The lack of trust, such as data breaches and obscured AI decisions, regulatory disjoints, and a lack of data sovereignty, keep threatening to ruin the potential of cloud AI ecosystems. This paper investigates the complex essence of trust under the framework of a data-driven and AI-enhanced cloud setup. It analytically discusses the technical, ethical, and governance aspects that are needed to build trustful, transparent, and safe cloud AI structures. The research hypothesizes an integrated trust framework based on the existing studies and unmet needs through synthesis and identification of gaps, which include progressive cryptographic algorithms, decentralized systems, auditable provenance systems, and ongoing AI monitoring. The manuscript has provided examples of the practical implementation of trust-enhancing technologies through illustrative case studies in the healthcare, finance, and smart city sectors. Lastly, it provides future projections of standardization, quantum-safe security, and ethical governance to establish a robust future of cloud computing. This publication is intended to serve as a roadmap to help researchers, practitioners, and policymakers build trust in an ever-connected, smarter digital environment.