Integrating artificial intelligence (AI) with multi-cloud architectures offers significant opportunities for organizations to enhance operational efficiency, scalability, and innovation. However, this integration presents challenges including managing multiple cloud platforms, addressing interoperability issues, ensuring data security and compliance, and mitigating performance variability. This systematic review examines the effectiveness of blockchain-based identity access management (IAM) in multi-cloud AI systems and identifies federation ethical controls governing responsible AI deployment. Analyzing 20 peer-reviewed studies published between 2015 and August 2025, we find that blockchain IAM reduces authentication latency by 47% while eliminating unauthorized access incidents in 90% of implementations. However, scalability challenges and implementation costs remain significant barriers. This comprehensive approach addresses growing concerns around data privacy in AI and machine learning, making it particularly attractive for businesses handling sensitive information or operating in highly regulated industries.